Hostname: page-component-586b7cd67f-2brh9 Total loading time: 0 Render date: 2024-11-24T10:34:26.378Z Has data issue: false hasContentIssue false
  • English
  • Français

Application of network methods for understanding mental disorders: pitfalls and promise

Published online by Cambridge University Press:  05 June 2017

S. Guloksuz ,
L-K. Pries  and
J. van Os
S. Guloksuz
Affiliation:
Department of Psychiatry and Psychology, Maastricht University Medical Centre, Maastricht, The Netherlands Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
L-K. Pries
Affiliation:
Department of Psychiatry and Psychology, Maastricht University Medical Centre, Maastricht, The Netherlands
J. van Os*
Affiliation:
Department of Psychiatry and Psychology, Maastricht University Medical Centre, Maastricht, The Netherlands King's College London, King's Health Partners, Department of Psychosis Studies, Institute of Psychiatry, London, UK
*
*Address for correspondence: J. van Os, Department of Psychiatry and Psychology, Maastricht University Medical Centre, P.O. BOX 616, 6200 MD Maastricht, The Netherlands. (Email: [email protected])
Get access Rights & Permissions [Opens in a new window]

Abstract

Galvanized with the availability of sophisticated statistical techniques and large datasets, network medicine has emerged as an active area of investigation. Following this trend, network methods have been utilized to understand the interplay between symptoms of mental disorders. This realistic approach that may provide an improved framework into understanding mental conditions and underlying mechanisms is certainly to be welcomed. However, we have noticed that symptom network studies tend to lose sight of the fundamentals, overlook major limitations embedded in study designs, and make inferences that are difficult to justify with current findings. There is concern that disregarding these flaws may halt the progress of the network approach in psychiatry. Therefore, in this paper, we first attempt to identify the pitfalls: (1) a reductionist understanding of medicine and psychiatry, thereby inadvertently reintroducing the dichotomy of medicine (lung cancer) and psychiatry (depression), (2) a shortsighted view of signs and symptoms, (3) overlooking the limitations of available datasets based on scales with embedded latent class structures, (4) overestimating the importance of the current findings beyond what is supported by the study design. By addressing current issues, the hope is to navigate this rapidly growing field to a more methodologically sound and reproducible path that will contribute to our understanding of mental disorders and its underlying mechanisms.

Keywords

DepressiondiagnosisDSMexperience sampling methodnetwork approachpsychopathology
Type
Review Article
Information
Psychological Medicine , Volume 47 , Issue 16 , December 2017 , pp. 2743 - 2752
Copyright
Copyright © Cambridge University Press 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Adams, D (2014). Dirk Gently's Holistic Detective Agency. Gallery Books: New York.Google Scholar
Atbasoglu, EC, Guloksuz, S (2013). Science, psychiatry, and the DSM. Turkish Journal of Psychiatry 24, 202–212.Google ScholarPubMed
Bak, M, Drukker, M, Hasmi, L, van Os, J (2016). An n=1 clinical network analysis of symptoms and treatment in psychosis. PLoS ONE 11, e0162811.CrossRefGoogle Scholar
Barabási, A-L, Gulbahce, N, Loscalzo, J (2011). Network medicine: a network-based approach to human disease. Nature Reviews Genetics 12, 56–68.CrossRefGoogle ScholarPubMed
Beard, C, Millner, AJ, Forgeard, MJ, Fried, EI, Hsu, KJ, Treadway, MT, Leonard, CV, Kertz, SJ, Bjorgvinsson, T (2016). Network analysis of depression and anxiety symptom relationships in a psychiatric sample. Psychological Medicine 46, 3359–3369.CrossRefGoogle Scholar
Bhatt, M, Kant, S, Bhaskar, R (2012). Pulmonary tuberculosis as differential diagnosis of lung cancer. South Asian Journal of Cancer 1, 36–42.Google ScholarPubMed
Boccaletti, S, Bianconi, G, Criado, R, Del Genio, CI, Gómez-Gardenes, J, Romance, M, Sendina-Nadal, I, Wang, Z, Zanin, M (2014). The structure and dynamics of multilayer networks. Physics Reports 544, 1–122.CrossRefGoogle ScholarPubMed
Borsboom, D (2017). A network theory of mental disorders. World Psychiatry 16, 5–13.CrossRefGoogle ScholarPubMed
Borsboom, D, Fried, F, Epskamp, S, Waldrop, L, van Borkulo, C, van der Maas, H, Cramer, A (2017). Psychopathology Networks Replicate with Stunning Precision (http://psychosystems.org/psychopathology-networks-replicate-with-stunning-precision/). Accessed 12 April 2017.Google Scholar
Bos, EH, Wanders, RB (2016). Group-level symptom networks in depression. JAMA Psychiatry 73, 411.CrossRefGoogle ScholarPubMed
Boschloo, L, van Borkulo, CD, Borsboom, D, Schoevers, RA (2016). A prospective study on how symptoms in a network predict the onset of depression. Psychotherapy and Psychosomatics 85, 183–184.CrossRefGoogle Scholar
Bringmann, L, Lemmens, L, Huibers, M, Borsboom, D, Tuerlinckx, F (2015). Revealing the dynamic network structure of the Beck Depression Inventory-II. Psychological Medicine 45, 747–757.CrossRefGoogle ScholarPubMed
Bryant, RA, Creamer, M, O'donnell, M, Forbes, D, McFarlane, AC, Silove, D, Hadzi-Pavlovic, D (2017). Acute and chronic posttraumatic stress symptoms in the emergence of posttraumatic stress disorder: a network analysis. JAMA Psychiatry 74, 135–142.CrossRefGoogle ScholarPubMed
Cooley, ME (2000). Symptoms in adults with lung cancer: a systematic research review. Journal of Pain and Symptom Management 19, 137–153.CrossRefGoogle ScholarPubMed
Cramer, AO, Borsboom, D, Aggen, SH, Kendler, KS (2012). The pathoplasticity of dysphoric episodes: differential impact of stressful life events on the pattern of depressive symptom inter-correlations. Psychological Medicine 42, 957–965.CrossRefGoogle ScholarPubMed
Eklund, A, Nichols, TE, Knutsson, H (2016). Cluster failure: why fMRI inferences for spatial extent have inflated false-positive rates. Proceedings of the National Academy of Sciences of the United States of America 113, 7900–7905.CrossRefGoogle ScholarPubMed
Forbes, MK, Wright, AG, Marjon, K, Krueger, R (in press). Evidence that psychopathology symptom networks do not replicate. Journal of Abnormal Psychology.Google Scholar
Fried, EI (2015). Problematic assumptions have slowed down depression research: why symptoms, not syndromes are the way forward. Frontiers in Psychology 6, 309.CrossRefGoogle Scholar
Fried, EI, Bockting, C, Arjadi, R, Borsboom, D, Amshoff, M, Cramer, AO, Epskamp, S, Tuerlinckx, F, Carr, D, Stroebe, M (2015). From loss to loneliness: the relationship between bereavement and depressive symptoms. Journal of Abnormal Psychology 124, 256–265.CrossRefGoogle ScholarPubMed
Fried, EI, Cramer, AO (2016). Moving forward: challenges and directions for psychopathological network theory and methodology. Perspectives on Psychological Science (https://osf.io/mh3cf/). Accessed 12 April 2017.Google Scholar
Fried, EI, Epskamp, S, Nesse, RM, Tuerlinckx, F, Borsboom, D (2016). What are ‘good’ depression symptoms? Comparing the centrality of DSM and non-DSM symptoms of depression in a network analysis. Journal of Affective Disorders 189, 314–320.CrossRefGoogle Scholar
Fried, EI, van Borkulo, CD, Cramer, AO, Boschloo, L, Schoevers, RA, Borsboom, D (2017). Mental disorders as networks of problems: a review of recent insights. Social Psychiatry and Psychiatric Epidemiology 52, 1–10.CrossRefGoogle ScholarPubMed
Friedberg, EC (2008). Sydney brenner. Nature Reviews Molecular Cell Biology 9, 8–9.CrossRefGoogle Scholar
Goh, K-I, Cusick, ME, Valle, D, Childs, B, Vidal, M, Barabási, A-L (2007). The human disease network. Proceedings of the National Academy of Sciences of the United States of America 104, 8685–8690.CrossRefGoogle ScholarPubMed
Guloksuz, S, van Os, J (2017). The slow death of the concept of schizophrenia. Manuscript submitted for publication.Google Scholar
Gustafsson, M, Nestor, CE, Zhang, H, Barabasi, AL, Baranzini, S, Brunak, S, Chung, KF, Federoff, HJ, Gavin, AC, Meehan, RR, Picotti, P, Pujana, MA, Rajewsky, N, Smith, KG, Sterk, PJ, Villoslada, P, Benson, M (2014). Modules, networks and systems medicine for understanding disease and aiding diagnosis. Genome Medicine 6, 82.CrossRefGoogle ScholarPubMed
Hidalgo, CA, Blumm, N, Barabasi, AL, Christakis, NA (2009). A dynamic network approach for the study of human phenotypes. PLoS Computational Biology 5, e1000353.CrossRefGoogle Scholar
Hood, L, Heath, JR, Phelps, ME, Lin, B (2004). Systems biology and new technologies enable predictive and preventative medicine. Science 306, 640–643.CrossRefGoogle ScholarPubMed
Hopwood, P, Stephens, RJ (2000). Depression in patients with lung cancer: prevalence and risk factors derived from quality-of-life data. Journal of Clinical Oncology 18, 893–893.CrossRefGoogle ScholarPubMed
Isvoranu, AM, Borsboom, D, van Os, J, Guloksuz, S (2016). A network approach to environmental impact in psychotic disorder: brief theoretical framework. Schizophrenia Bulletin 42, 870–873.CrossRefGoogle ScholarPubMed
Isvoranu, AM, van Borkulo, CD, Boyette, LL, Wigman, JT, Vinkers, CH, Borsboom, D, Group, I (2017). A network approach to psychosis: pathways between childhood trauma and psychotic symptoms. Schizophrenia Bulletin 43, 187–196.CrossRefGoogle ScholarPubMed
Jokela, M, Virtanen, M, Batty, GD, Kivimäki, M (2016). Inflammation and specific symptoms of depression. JAMA Psychiatry 73, 87–88.CrossRefGoogle ScholarPubMed
Kapur, S, Phillips, AG, Insel, TR (2012). Why has it taken so long for biological psychiatry to develop clinical tests and what to do about it? Molecular Psychiatry 17, 1174–1179.CrossRefGoogle Scholar
Kendler, KS (2016). The phenomenology of major depression and the representativeness and nature of DSM criteria. American Journal of Psychiatry 173, 771–780.CrossRefGoogle ScholarPubMed
Kendler, KS, Parnas, J (2015). Philosophical Issues in Psychiatry: Explanation, Phenomenology, and Nosology. JHU Press: Baltimore.Google Scholar
King, LS (1968). Signs and symptoms. JAMA 206, 1063–1065.CrossRefGoogle ScholarPubMed
Lublin, FD, Reingold, SC, Cohen, JA, Cutter, GR, Sørensen, PS, Thompson, AJ, Wolinsky, JS, Balcer, LJ, Banwell, B, Barkhof, F (2014). Defining the clinical course of multiple sclerosis The 2013 revisions. Neurology 83, 278–286.CrossRefGoogle ScholarPubMed
McGorry, P (2016). Early intervention: mission cramp versus mission creep? Aust N Z J Psychiatry 50, 1033–1035.CrossRefGoogle ScholarPubMed
McGorry, P, Nelson, B (2016). Why we need a transdiagnostic staging approach to emerging psychopathology, early diagnosis, and treatment. JAMA Psychiatry 73, 191–192.CrossRefGoogle Scholar
McNally, RJ (2016). Can network analysis transform psychopathology? Behaviour Research and Therapy 86, 95–104.CrossRefGoogle ScholarPubMed
McNally, RJ (2017). Networks and nosology in posttraumatic stress disorder. JAMA Psychiatry 74, 124–125.CrossRefGoogle ScholarPubMed
Miller, AH, Raison, CL (2016). The role of inflammation in depression: from evolutionary imperative to modern treatment target. Nature Reviews Immunology 16, 22–34.CrossRefGoogle Scholar
Munafò, MR, Nosek, BA, Bishop, DVM, Button, KS, Chambers, CD, Percie du Sert, N, Simonsohn, U, Wagenmakers, E-J, Ware, JJ, Ioannidis, JPA (2017). A manifesto for reproducible science. Nature Human Behaviour 1, 0021.CrossRefGoogle ScholarPubMed
National Research Council (2011). Toward Precision Medicine: Building a Knowledge Network for Biomedical Research and a New Taxonomy of Disease. National Academies Press: Washington.Google Scholar
Pao, W, Girard, N (2011). New driver mutations in non-small-cell lung cancer. Lancet Oncology 12, 175–180.CrossRefGoogle ScholarPubMed
Proctor, RN (2012). The history of the discovery of the cigarette–lung cancer link: evidentiary traditions, corporate denial, global toll. Tobacco Control 21, 87–91.CrossRefGoogle ScholarPubMed
Reyes-Gibby, CC, Swartz, MD, Yu, X, Wu, X, Yennurajalingam, S, Anderson, KO, Spitz, MR, Shete, S (2013). Symptom clusters of pain, depressed mood, and fatigue in lung cancer: assessing the role of cytokine genes. Supportive Care in Cancer 21, 3117–3125.CrossRefGoogle ScholarPubMed
Toh, C-K, Gao, F, Lim, W-T, Leong, S-S, Fong, K-W, Yap, S-P, Hsu, AA, Eng, P, Koong, H-N, Thirugnanam, A (2006). Never-smokers with lung cancer: epidemiologic evidence of a distinct disease entity. Journal of Clinical Oncology 24, 2245–2251.CrossRefGoogle ScholarPubMed
van Borkulo, C, Boschloo, L, Borsboom, D, Penninx, BW, Waldorp, LJ, Schoevers, RA (2015). Association of symptom network structure with the course of depression. JAMA Psychiatry 72, 1219–1226.CrossRefGoogle Scholar
Van Den Heuvel, MP, Pol, HEH (2010). Exploring the brain network: a review on resting-state fMRI functional connectivity. European Neuropsychopharmacology 20, 519–534.CrossRefGoogle ScholarPubMed
van Os, J (2013). The dynamics of subthreshold psychopathology: implications for diagnosis and treatment. American Journal of Psychiatry 170, 695–698.CrossRefGoogle ScholarPubMed
van Os, J (2015). Mental disorder: a public health problem stuck in an individual-level brain disease perspective? World Psychiatry 14, 47–48.CrossRefGoogle Scholar
van Os, J, Verhagen, S, Marsman, A, Peeters, F, Bak, M, Marcelis, M, Drukker, M, Reininghaus, U, Jacobs, N, Lataster, T, Simons, C, ESM-MERGE investigators, Lousberg, R, Guloksuz, S, Leue, C, Groot, PC, Viechtbauer, W, Delespaul, P (2017). The experience sampling method as an mHealth tool to support self-monitoring, self-insight and personalised health care in clinical practice. Depression and Anxiety (in press).CrossRefGoogle ScholarPubMed
Verhagen, SJ, Hasmi, L, Drukker, M, van Os, J, Delespaul, PA (2016). Use of the experience sampling method in the context of clinical trials. Evidence Based Mental Health 19, 86–89.CrossRefGoogle ScholarPubMed
Vidal, M, Cusick, ME, Barabasi, A-L (2011). Interactome networks and human disease. Cell 144, 986–998.CrossRefGoogle ScholarPubMed
Wichers, M, Wigman, JT, Bringmann, LF, de Jonge, P (2017). Mental disorders as networks: some cautionary reflections on a promising approach. Social Psychiatry and Psychiatric Epidemiology 52, 143–145.CrossRefGoogle ScholarPubMed
Wigman, JT, de Vos, S, Wichers, M, van Os, J, Bartels-Velthuis, AA (2017). A transdiagnostic network approach to psychosis. Schizophrenia Bulletin 43, 122–132.CrossRefGoogle ScholarPubMed
Wigman, JT, van Os, J, Borsboom, D, Wardenaar, KJ, Epskamp, S, Klippel, A, MERGE, Viechtbauer, W, Myin-Germeys, I, Wichers, M (2015). Exploring the underlying structure of mental disorders: cross-diagnostic differences and similarities from a network perspective using both a top-down and a bottom-up approach. Psychological Medicine 45, 2375–2387.CrossRefGoogle ScholarPubMed
Zhou, X, Menche, J, Barabasi, AL, Sharma, A (2014). Human symptoms-disease network. Nature Communications 5, 4212.CrossRefGoogle ScholarPubMed