The heterogeneity of the depressive syndrome: when numbers get serious
Open accessAbstract
The current criteria for major depression (1) have been criticized for the heterogeneity of the clinical syndrome they define. This has led to suggestions of alternative classifications, most recently by G. Parker in this journal (2). According to the critics, the polymorphic syndrome is partly to blame for the fact that the treatment of depression still has not moved beyond the trial and error approach and that the genetics and neurobiology underlying the depressive disorder still remain largely unknown and without practical significance (3). Two of the most interesting studies on major depression, conducted within recent years, reflect this problem: In the STAR*D study, which included more than 4000 subjects with major depression, only 30% of the patients remitted on treatment with a current first-line antidepressant drug (Citalopram) and other 30% did not remit after four consecutive treatment trials with antidepressants from different pharmacological classes - despite a formalized and aggressive dosing strategy (4). The hypothesis of increased risk for depression caused by an interaction between the serotonin transporter promoter gene polymorphism (5-HTTLPR) and 'adverse life events', such as childhood maltreatment and medical conditions, has been subjected to intense debate over the past decade. Does the interaction take place or not? This discussion may come to an end after the publication of a recent meta-analysis by Karg et al. (5), which is based on more than 40 000 subjects. The results of the meta-analysis suggest that the 5-HTTLPR - adverse life event - interaction does increase the risk of depression. What can be learned from these two large-scale studies? The fact that only 30% of patients remitted on a second-generation antidepressant is probably not because the drug does not work. Likewise, the fact that it took more than 40 000 subjects to 'prove' the interaction between the serotonin transporter gene and adverse life events is probably not because such interaction does not have an impact on the risk of developing depression. The underlying reason for these rather disappointing results is likely to lie in the heterogeneity of the depressive syndrome. The subjects included in the two studies are probably so dissimilar that any relevant causal effect of risk factors and clinical benefit of treatments are lost in the flood. But exactly how heterogeneous is the depressive syndrome? To give a theoretical answer to this question, we applied simple combinatorics to the nine symptoms considered in the DSM-IV criteria (1): Depressed mood Markedly diminished interest or pleasure Significant weight loss or weight gain Insomnia or hypersomnia Psychomotor agitation or retardation Fatigue or loss of energy Feelings of worthlessness or excessive or inappropriate guilt Diminished ability to think or concentrate or indecisiveness Recurrent thoughts of death or recurrent suicidal ideation The binomial coefficient calculates the number of subsets of k draws from n distinguishable objects without replacement and without regard to order. The result is 227 different combinations with ≥5 symptoms, but this is not the full picture. At least four of the DSM-IV symptoms actually cover two distinct symptoms each: 'weight loss or weight gain', 'insomnia or hypersomnia', 'psychomotor agitation or retardation' and 'feelings of worthlessness or inappropriate guilt'. When these, quite different, individual symptoms are taken into account, the resulting number of combinations is 1497, without considering the psychotic subtype of depression (delusions, hallucinations, or both) or the fact that depressive episodes can occur in both unipolar and bipolar courses of illness. Furthermore, it can be argued that the core symptom 'diminished interest or pleasure' also covers two different symptoms. Thus, the 1497 combinations are actually a conservative estimate. These calculations may be considered as mere academic exercise, but they also prove a point, namely that the current depressive syndrome is at least very, if not too, heterogeneous. Obviously, some of the 1497 combinations have a considerable overlap, but on the other hand, patients fulfilling the diagnostic criteria do not necessarily share any symptoms at all: John, a former successful CEO of a large company, developed depression after the bankruptcy of his company, which led to his firing and subsequent divorce. John has no relatives with depression or other mental disorders. Alice, graduate student in psychology, developed depression without any external stressors. There is a strong family history of depression and bipolar disorder in her family. The clinical pictures of John and Alice are quite different, yet both patients may have been included as subjects in the STAR*D (4) and the gene-environment study by Karg et al. (5). With this degree of heterogeneity among participants in depression-trials, it is not a major surprise that researchers are struggling to tease ou
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Major depressive disorder is a vastly heterogeneous syndrome.
“Major depressive disorder (MDD) is a vastly heterogeneous syndrome [7]”
From Effects of escitalopram on synaptic density in the healthy human brain: a randomized controlled trial (2023) · cites this paper as [7]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR)
American Psychiatric Association (2000) · doi:10.1176/appi.books.9780890423349 · Cited by 11,069 · see citing works
Gaynes, B. N., Warden, D., Trivedi, M. H., Wisniewski, S. R., Fava, M., & Rush, A. J. (2009) · Psychiatric Services · doi:10.1176/ps.2009.60.11.1439 · Cited by 661 · see citing works
Stuck in a rut: rethinking depression and its treatment
Holtzheimer, P. E., & Mayberg, H. S. (2010) · Trends in Neurosciences · doi:10.1016/j.tins.2010.10.004 · Cited by 431 · see citing works
Karg, K., Burmeister, M., Shedden, K., & Sen, S. (2011) · Archives of General Psychiatry · doi:10.1001/archgenpsychiatry.2010.189 · Cited by 87 · see citing works
Classifying clinical depression: an operational proposal
Parker, G. B. (2011) · Acta Psychiatrica Scandinavica · doi:10.1111/j.1600-0447.2011.01681.x · Cited by 31 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Gut microbiome and depression: what we know and what we need to know
Winter, G., Hart, R. A., Charlesworth, R. P. G., & Sharpley, C. F. (2018) · Reviews in the Neurosciences · doi:10.1515/revneuro-2017-0072 · Cited by 394 · see citing works
Moriguchi, S., Takamiya, A., Noda, Y., Horita, N., Wada, M., Tsugawa, S., Plitman, E., Sano, Y., Tarumi, R., ElSalhy, M., et al. (2019) · Molecular Psychiatry · doi:10.1038/s41380-018-0252-9 · Cited by 357 · see citing works
An adaptationist perspective on the etiology of depression
Durisko, Z., Mulsant, B. H., & Andrews, P. W. (2015) · Journal of Affective Disorders · doi:10.1016/j.jad.2014.09.032 · Cited by 140 · see citing works
The use of latent class analysis for identifying subtypes of depression: a systematic review
Ulbricht, C. M., Chrysanthopoulou, S. A., Levin, L., & Lapane, K. L. (2018) · Psychiatry Research · doi:10.1016/j.psychres.2018.03.003 · Cited by 138 · see citing works
Perez, N., Langlest, F., Mallet, L., De Pieri, M., Sentissi, O., Thorens, G., Seragnoli, F., Zullino, D., Kirschner, M., Kaiser, S., et al. (2023) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2023.07.011 · Cited by 88 · see citing works
“Moreover, while these robust findings allow us to extract a dose-response curve for effi-cacy, there is often significant heterogeneity in the depres-72 sive syndromes included in clinical trials ( Østergaard et al., 2011 ).”
Sleep deprivation as treatment for depression: systematic review and meta-analysis
Ioannou, M., Wartenberg, C., Greenbrook, J. T. V., Larson, T., Magnusson, K., Schmitz, L., Sjögren, P., Stadig, I., Szabó, Z., & Steingrimsson, S. (2021) · Acta Psychiatrica Scandinavica · doi:10.1111/acps.13253 · Cited by 75 · see citing works
The heterogeneity of depression: an old debate renewed
Ghaemi, S. N., & Vöhringer, P. A. (2011) · Acta Psychiatrica Scandinavica · doi:10.1111/j.1600-0447.2011.01746.x · Cited by 52 · see citing works
Emotional blunting in patients with depression. Part I: clinical characteristics
Christensen, M. C., Ren, H., & Fagiolini, A. (2022) · Annals of General Psychiatry · doi:10.1186/s12991-022-00387-1 · Cited by 53 · see citing works
Johansen, A., Armand, S., Plavén-Sigray, P., Nasser, A., Ozenne, B., Petersen, I. N., Keller, S. H., Madsen, J., Beliveau, V., Møller, K., et al. (2023) · Molecular Psychiatry · doi:10.1038/s41380-023-02285-8 · Cited by 53 · see citing works
Chokka, P., Bougie, J., Rampakakis, E., & Proulx, J. (2019) · CNS Spectrums · doi:10.1017/s1092852918000913 · Cited by 48 · see citing works
Abbas, A., Sauder, C., Yadav, V., Koesmahargyo, V., Aghjayan, A., Marecki, S., Evans, M., & Galatzer-Levy, I. R. (2021) · Frontiers in Digital Health · doi:10.3389/fdgth.2021.610006 · Cited by 49 · see citing works
Elevated body temperature is associated with depressive symptoms: results from the TemPredict Study
Mason, A. E., Kasl, P., Soltani, S., Green, A., Hartogensis, W., Dilchert, S., Chowdhary, A., Pandya, L. S., Siwik, C. J., Foster, S. L., et al. (2024) · Scientific Reports · doi:10.1038/s41598-024-51567-w · Cited by 31 · see citing works
Euteneuer, F., Schwarz, M. J., Dannehl, K., Hartung, A., Westermann, S., & Rief, W. (2012) · Brain, Behavior, and Immunity · doi:10.1016/j.bbi.2012.06.007 · Cited by 25 · see citing works
Sex differences in the mediators of functional disability in Major Depressive Disorder
Carmona, N. E., Subramaniapillai, M., Mansur, R. B., Cha, D. S., Lee, Y., Fus, D., & McIntyre, R. S. (2018) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2017.09.025 · Cited by 22 · see citing works
Unpacking Associations between Mood Symptoms and Screen Time in Preadolescents: a Network Analysis
Lin, S.-Y., Eaton, N. R., & Schleider, J. L. (2020) · Journal of Abnormal Child Psychology · doi:10.1007/s10802-020-00703-x · Cited by 19 · see citing works
- Authors
- Østergaard, S. D., Jensen, S. O. W., & Bech, P.
- Affiliations
- Aarhus University Hospital (DK)
- Copenhagen University Hospital (DK)
- Corresponding author
- Bech, P.
- Venue
- Acta Psychiatrica Scandinavica
- Publisher
- Wiley
- Published
- 2011-08-13
- Volume
- 124
- Issue
- 6
- Pages
- 495-496
- ISSN
- 0001-690X (ISSN-L)
- 1600-0447
- OpenAlex
- W1509211586
- Cited by
- 287
- References
- 5
- Citations by year
- 2026: 13 · 2025: 21 · 2024: 23 · 2023: 29 · 2022: 16 · 2021: 29 · 2020: 28 · 2019: 16 · 2018: 19 · 2017: 16 · 2016: 20 · 2015: 17 · 2014: 17 · 2013: 13 · 2012: 6
- FWCI
- 9.37
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Acta Psychiatrica Scandinavica (publishedVersion)
- PubMed (publishedVersion)
- Research at the University of Copenhagen (University of Copenhagen) (submittedVersion)
- Topics
- Health Sciences › Medicine › Pharmacology › Treatment of Major Depression
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurotransmitter Receptor Influence on Behavior
- Keywords
- major depressive disorder, antidepressant response, 5-HTTLPR, serotonin transporter gene polymorphism, life events, child abuse, genetic risk factors, DSM-IV diagnostic criteria, depression classification, treatment-resistant depression, remission rate
- MeSH terms
- Clinical Trials as Topic, Depressive Disorder, Major, Major Depressive Disorder, Humans, Psychometrics, Dissent and Disputes, Genetic Research
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review