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Aiding the diagnosis of dissociative identity disorder: pattern recognition study of brain biomarkers

  • Antje A. T. S. Reinders (a1), Andre F. Marquand (a2), Yolanda R. Schlumpf (a3), Sima Chalavi (a4), Eline M. Vissia (a5), Ellert R. S. Nijenhuis (a6), Paola Dazzan (a7), Lutz Jäncke (a8) and Dick J. Veltman (a9)...

Abstract

Background

A diagnosis of dissociative identity disorder (DID) is controversial and prone to under- and misdiagnosis. From the moment of seeking treatment for symptoms to the time of an accurate diagnosis of DID individuals received an average of four prior other diagnoses and spent 7 years, with reports of up to 12 years, in mental health services.

Aim

To investigate whether data-driven pattern recognition methodologies applied to structural brain images can provide biomarkers to aid DID diagnosis.

Method

Structural brain images of 75 participants were included: 32 female individuals with DID and 43 matched healthy controls. Individuals with DID were recruited from psychiatry and psychotherapy out-patient clinics. Probabilistic pattern classifiers were trained to discriminate cohorts based on measures of brain morphology.

Results

The pattern classifiers were able to accurately discriminate between individuals with DID and healthy controls with high sensitivity (72%) and specificity (74%) on the basis of brain structure. These findings provide evidence for a biological basis for distinguishing between DID-affected and healthy individuals.

Conclusions

We propose a pattern of neuroimaging biomarkers that could be used to inform the identification of individuals with DID from healthy controls at the individual level. This is important and clinically relevant because the DID diagnosis is controversial and individuals with DID are often misdiagnosed. Ultimately, the application of pattern recognition methodologies could prevent unnecessary suffering of individuals with DID because of an earlier accurate diagnosis, which will facilitate faster and targeted interventions.

Declaration of interest

The authors declare no competing financial interests.

Copyright

Corresponding author

Correspondence: Antje A. T. S. Reinders, Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, De Crespigny Park, London SE5 8AZ, UK. Email: a.a.t.s.reinders@kcl.ac.uk

Footnotes

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*

These authors contributed equally to this article.

These authors contributed equally to this article.

Footnotes

References

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1Gillig, PM. Dissociative identity disorder: a controversial diagnosis. Psychiatry 2009; 6: 24–9.
2Dalenberg, CJ, Brand, BL, Loewenstein, RJ, Gleaves, DH, Dorahy, MJ, Cardeña, E, et al. Reality versus fantasy: reply to Lynn et al. (2014). Psychol Bull 2014; 140: 911–20.
3Brand, BL, Vissia, EM, Chalavi, S, Nijenhuis, ERS, Webermann, AR, Draijer, N, et al. DID is trauma based: further evidence supporting the trauma model of DID. Acta Psychiatr Scand 2016; 134: 560–3.
4International Society for the Study of Trauma and Dissociation. Guidelines for treating dissociative identity disorder in adults, third revision. J Trauma Dissociation 2011; 12: 115–87.
5Piper, A, Merskey, H. The persistence of folly: a critical examination of dissociative identity disorder. Part I. The excesses of an improbable concept. Can J Psychiatry 2004; 49: 592600.
6Pope, HG, Barry, S, Bodkin, A, Hudson, JI. Tracking scientific interest in the dissociative disorders: a study of scientific publication output 1984-2003. Psychother Psychosom 2006; 75: 1924.
7Sar, V. Epidemiology of dissociative disorders: an overview. Epidemiol Res Int 2011; 1: 18.
8Lloyd, M. Reducing the cost of dissociative identity disorder: measuring the effectiveness of specialized treatment by frequency of contacts with mental health services. J Trauma Dissociation 2016; 17: 362–70.
9Myrick, AC, Webermann, AR, Langeland, W, Putnam, FW, Brand, BL. Treatment of dissociative disorders and reported changes in inpatient and outpatient cost estimates. Eur J Psychotraumatol 2017; 8: 1375829.
10Wolfers, T, Buitelaar, JK, Beckmann, C, Franke, B, Marquand, AF. From estimating activation locality to predicting disorder: a review of pattern recognition for neuroimaging-based psychiatric diagnostics. Neurosci Biobehav Rev 2015; 57: 328–49.
11Vissia, EM, Giesen, ME, Chalavi, S, Nijenhuis, ERS, Draijer, N, Brand, BL, et al. Is it Trauma- or Fantasy-based? Comparing dissociative identity disorder, post-traumatic stress disorder, simulators, and controls. Acta Psychiatr Scand 2016; 134: 111–28.
12Schlumpf, YR, Nijenhuis, ERS, Chalavi, S, Weder, EV, Zimmermann, E, Luechinger, R, et al. Dissociative part-dependent biopsychosocial reactions to backward masked angry and neutral faces: an fMRI study of dissociative identity disorder. NeuroImage Clin 2013; 3: 5464.
13Schlumpf, YR, Reinders, AATS, Nijenhuis, ERS, Luechinger, R, van Osch, MJP, Jäncke, L. Dissociative part-dependent resting-state activity in dissociative identity disorder: a controlled FMRI perfusion study. PLoS One 2014; 9: e98795.
14Reinders, AATS, Willemsen, ATM, Vissia, EM, Vos, HPJ, den Boer, JA, Nijenhuis, ERS. The psychobiology of authentic and simulated dissociative personality states: the full Monty. J Nerv Ment Dis 2016; 204: 445–57.
15Zotev, V, Phillips, R, Young, KD, Drevets, WC, Bodurka, J. Prefrontal control of the amygdala during real-time fMRI neurofeedback training of emotion regulation. PLoS One 2013; 8: e79184.
16Kim, S, Birbaumer, N. Real-time functional MRI neurofeedback: a tool for psychiatry. Curr Opin Psychiatry 2014; 27: 332–6.
17Chalavi, S, Vissia, EM, Giesen, ME, Nijenhuis, ERS, Draijer, N, Barker, GJ, et al. Similar cortical but not subcortical gray matter abnormalities in women with posttraumatic stress disorder with versus without dissociative identity disorder. Psychiatry Res 2015; 231: 308–19.
18Chalavi, S, Vissia, EM, Giesen, ME, Nijenhuis, ERS, Draijer, N, Cole, JH, et al. Abnormal hippocampal morphology in dissociative identity disorder and post-traumatic stress disorder correlates with childhood trauma and dissociative symptoms. Hum Brain Mapp 2015; 36: 1692–704.
19Reinders, AATS, Chalavi, S, Schlumpf, YR, Vissia, EM, Nijenhuis, ERS, Jäncke, L, et al. Neurodevelopmental origins of abnormal cortical morphology in dissociative identity disorder. Acta Psychiatr Scand 2018; 137: 157–70.
20American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, DSM-5 (5th edn). American Psychiatric Association, 2013.
21Boon, S, Draijer, N. Multiple personality disorder in The Netherlands: a clinical investigation of 71 patients. Am J Psychiatry 1993; 150: 489–94.
22Steinberg, M. Structured Clinical Interview for DSM-IV Dissociative Disorders (SCID-D). American Psychiatric Press, 1993.
23Draijer, N, Boon, S. The imitation of dissociative identity disorder: patients at risk, therapists at risk. J Psychiatry Law 1999; 27: 423–58.
24Rodewald, F, Wilhelm-Göling, C, Emrich, HM, Reddemann, L, Gast, U. Axis-I comorbidity in female patients with dissociative identity disorder and dissociative identity disorder not otherwise specified. J Nerv Ment Dis 2011; 199: 122–31.
25Bozkurt, H, Duzman Mutluer, T, Kose, C, Zoroglu, S. High psychiatric comorbidity in adolescents with dissociative disorders. Psychiatry Clin Neurosci 2015; 69: 369–74.
26Bernstein, EM, Putnam, FW. Development, reliability, and validity of a dissociation scale. J Nerv Ment Dis 1986; 174: 727–35.
27Nijenhuis, ERS, Spinhoven, P, Van Dyck, R, Van der Hart, O, Vanderlinden, J. The development and psychometric characteristics of the Somatoform Dissociation Questionnaire (SDQ-20). J Nerv Ment Dis 1996; 184: 688–94.
28Sierra, M, Berrios, GE. The Cambridge Depersonalization Scale: a new instrument for the measurement of depersonalization. Psychiatry Res 2000; 93: 153–64.
29Nijenhuis, ERS, Van der Hart, O, Kruger, K. The psychometric characteristics of the Traumatic Experiences Checklist (TEC): first findings among psychiatric outpatients. Clin Psychol Psychother 2002; 9: 200–10.
30Chalavi, S, Simmons, A, Dijkstra, H, Barker, GJ, Reinders, AA. Quantitative and qualitative assessment of structural magnetic resonance imaging data in a two-center study. BMC Med Imaging 2012; 12: 27.
31Ashburner, J, Friston, KJ. Unified segmentation. Neuroimage 2005; 26: 839–51.
32Ashburner, J, Friston, KJ. Computing average shaped tissue probability templates. Neuroimage 2009; 45: 333–41.
33Ashburner, J, Friston, KJ. Diffeomorphic registration using geodesic shooting and Gauss-Newton optimisation. Neuroimage 2011; 55: 954–67.
34Singh, N, Fletcher, PT, Preston, JS, Ha, L, King, R, Marron, JS, et al. Multivariate Statistical Analysis of Deformation Momenta Relating Anatomical Shape to Neuropsychological Measures. In 13th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI, 2010: 529–37.
35Marquand, AF, Filippone, M, Ashburner, J, Girolami, M, Mourao-Miranda, J, Barker, GJ, et al. Automated, high accuracy classification of parkinsonian disorders: a pattern recognition approach. PLoS One 2013; 8: e69237.
36Rasmussen, CE, Williams, CKI. Gaussian Processes for Machine Learning. University Press Group Limited, 2006.
37Marquand, A, Howard, M, Brammer, M, Chu, C, Coen, S, Mourão-Miranda, J. Quantitative prediction of subjective pain intensity from whole-brain fMRI data using Gaussian processes. Neuroimage 2010; 49: 2178–89.10.1016/j.neuroimage.2009.10.072
38Orrù, G, Pettersson-Yeo, W, Marquand, AF, Sartori, G, Mechelli, A. Using Support Vector Machine to identify imaging biomarkers of neurological and psychiatric disease: a critical review. Neurosci Biobehav Rev 2012; 36: 1140–52.
39Schrouff, J, Rosa, MJ, Rondina, JM, Marquand, AF, Chu, C, Ashburner, J, et al. PRoNTo: pattern recognition for neuroimaging toolbox. Neuroinformatics 2013; 11: 319.
40Hahn, T, Marquand, AF, Plichta, MM, Ehlis, A-C, Schecklmann, MW, Dresler, T, et al. A novel approach to probabilistic biomarker-based classification using functional near-infrared spectroscopy. Hum Brain Mapp 2013; 34: 1102.
41Lim, HK, Jung, WS, Ahn, KJ, Won, WY, Hahn, C, Lee, SY, et al. Regional cortical thickness and subcortical volume changes are associated with cognitive impairments in the drug-naive patients with late-onset depression. Neuropsychopharmacology 2012; 37: 838–49.
42Haufe, S, Meinecke, F, Gorgen, K, Dahne, S, Haynes, J-D, Blankertz, B, et al. On the interpretation of weight vectors of linear models in multivariate neuroimaging. Neuroimage 2014; 87: 96110.
43Mourão-Miranda, J, Bokde, ALW, Born, C, Hampel, H, Stetter, M. Classifying brain states and determining the discriminating activation patterns: support Vector Machine on functional MRI data. Neuroimage 2005; 28: 980–95.
44Avants, BB, Tustison, NJ, Song, G, Cook, PA, Klein, A, Gee, JC. A reproducible evaluation of ANTs similarity metric performance in brain image registration. Neuroimage 2011; 54: 2033–44.
45Foote, B, Smolin, Y, Kaplan, M, Legatt, ME, Lipschitz, D. Prevalence of dissociative disorders in psychiatric outpatients. Am J Psychiatry 2006; 163: 623–9.
46Sar, V, Akyüz, G, Doğan, O. Prevalence of dissociative disorders among women in the general population. Psychiatry Res 2007; 149: 169–76.
47Dorahy, MJ, Brand, BL, Sar, V, Krüger, C, Stavropoulos, P, Martínez-Taboas, A, et al. Dissociative identity disorder: an empirical overview. Aust N Z J Psychiatry 2014; 48: 402–17.10.1177/0004867414527523
48Mourao-Miranda, J, Reinders, AATS, Rocha-Rego, V, Lappin, J, Rondina, J, Morgan, C, et al. Individualized prediction of illness course at the first psychotic episode: a support vector machine MRI study. Psychol Med 2012; 42: 1037–47.10.1017/S0033291711002005
49Nardo, D, Högberg, G, Lanius, RA, Jacobsson, H, Jonsson, C, Hällström, T, et al. Gray matter volume alterations related to trait dissociation in PTSD and traumatized controls. Acta Psychiatr Scand 2013; 128: 222–33.
50Sierra, M, Nestler, S, Jay, E-L, Ecker, C, Feng, Y, David, AS. A structural MRI study of cortical thickness in depersonalisation disorder. Psychiatry Res Neuroimaging 2014; 224: 17.
51Daniels, JK, Frewen, P, Theberge, J, Lanius, RA. Structural brain aberrations associated with the dissociative subtype of post-traumatic stress disorder. Acta Psychiatr Scand 2016; 133: 232–40.
52Lanius, RA, Vermetten, E, Loewenstein, RJ, Brand, B, Schmahl, C, Bremner, JD, et al. Emotion modulation in PTSD: clinical and neurobiological evidence for a dissociative subtype. Am J Psychiatry 2010; 167: 640–7.
53Lemche, E, Anilkumar, A, Giampietro, VP, Brammer, MJ, Surguladze, SA, Lawrence, NS, et al. Cerebral and autonomic responses to emotional facial expressions in depersonalisation disorder. Br J Psychiatry 2008; 193: 222–8.
54Gong, Q, Li, L, Tognin, S, Wu, Q, Pettersson-Yeo, W, Lui, S, et al. Using structural neuroanatomy to identify trauma survivors with and without post-traumatic stress disorder at the individual level. Psychol Med 2014; 44: 195203.

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Aiding the diagnosis of dissociative identity disorder: pattern recognition study of brain biomarkers

  • Antje A. T. S. Reinders (a1), Andre F. Marquand (a2), Yolanda R. Schlumpf (a3), Sima Chalavi (a4), Eline M. Vissia (a5), Ellert R. S. Nijenhuis (a6), Paola Dazzan (a7), Lutz Jäncke (a8) and Dick J. Veltman (a9)...
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