Distinguishing affective depersonalization from anhedonia in major depression and bipolar disorder

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Comprehensive Psychiatry 51 (2010) 187 – 192 www.elsevier.com/locate/comppsych

Distinguishing affective depersonalization from anhedonia in major depression and bipolar disorder Marco Mulaa,⁎, Stefano Pinia , Simona Calugia , Matteo Prevea , Matteo Masinia , Ilaria Giovanninia , Paola Ruccib , Giovanni B. Cassanoa a

Department of Psychiatry, Neurobiology, Pharmacology and Biotechnologies, University of Pisa, 56100 Pisa, Italy b Department of Medicine and Public Health, University of Bologna, Bologna, Italy

Abstract Background: Affective depersonalization has received limited attention in the literature, although its conceptualization may have implications in terms of identification of clinical endophenotypes of mood disorders. Thus, this study aims to test the hypothesis that anhedonia and affective depersonalization represent 2 distinct psychopathological dimensions and to investigate their clinical correlates in patients with major depressive disorder (MDD) and bipolar disorder (BD). Methods: Using a data pool of 258 patients with mood and anxiety disorders, an item response theory–based factor analysis approach was carried out on 16 items derived from 2 clinical instruments developed in the Spectrum Project (the Structured Clinical Interview for Mood Spectrum and the Structured Clinical Interview for Derealization-Depersonalization Spectrum). Clinical correlates of these psychometrically derived dimensions were subsequently investigated in patients with BD or MDD. Results: Using an item response theory–based factor analysis, a 2-factor solution was identified, accounting overall for the 47.0% of the variance. Patients with BD showed statistically significant higher affective depersonalization factor scores than those with MDD (Z = 2.215, P = .027), whereas there was no between-groups difference in anhedonia scores (Z = 0.825 P = .411). In patients with BD, age of onset of the disease correlated with affective depersonalization factor scores (ρ = −0.330, P = .001) but not with anhedonia factor scores (ρ = −0.097, P = .361). Conclusions: Affective depersonalization and anhedonia seem to be 2 distinct psychopathological dimensions, although closely related, bearing the opportunity to identify patients with a specific profile for a better clinical and neurobiological definition. © 2010 Elsevier Inc. All rights reserved.

1. Introduction Current diagnostic practice is guided by Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV), which provides a polythetic, categorical approach to classification of psychiatric disorders, currently validated by empirical studies. However, DSM-IV classification has some important limitations. Among them is the failure of a categorical system to capture specific manifestations associated with a given disorder. The dimensional approach to psychiatric disorders has been proposed as complementary to the classical categorical one, for a better definition of clinical endophenotypes in terms of prognosis and better tailored therapies [1-4]. Moreover, psychopatho⁎ Corresponding author. Department of Clinical & Experimental Medicine, Section of Neurology, Amedeo Avogadro University C.so Mazzini, 18 28100 Novara, Italy. Tel.: +39 03213733371; fax: +39 03213733298. E-mail address: [email protected] (M. Mula). 0010-440X/$ – see front matter © 2010 Elsevier Inc. All rights reserved. doi:10.1016/j.comppsych.2009.03.009

logical dimensions have been claimed to have a much more apparent biological foundation [5]. Although it can be assumed that specific psychopathological dimensions involve physiologic arousal, appraisal, subjective experience, and goal directed behavior, there is still limited understanding of their neurobiological bases [6]. This is partly due to the complexity of distinguishing psychopathological constructs that have a wide overlap. Depression involves several psychopathological components, and different authors adopted a factor analysis approach to obtain a map of symptom components of depression [7-11]. However, the identification of specific dimensions is strictly related to the adopted assessment instrument. Although anhedonia is recognized as an important component of depression [12-14] and is one of the diagnostic criteria for the DSM-IV diagnosis of major depression with melancholia [15], affective depersonalization (AD) is not specifically investigated by most clinical instruments used to assess patients with mood disorders.

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Anhedonia is defined as a diminished or abolished capacity to experience pleasant emotions and was introduced as one of the core symptoms of the endogenous (or melancholic) subtype of major depression in DSM-III [16]. The development of anhedonia as a construct was influenced by Klein's conceptual framework of “endogenomorphic” depression, which referred to a particular type of depression characterized by a pervasive impairment of the capacity to experience pleasure or to respond affectively to the anticipation of pleasure [17]. Anhedonia was found to correlate significantly with neuroticism, introversion, and morbid risk of depression in first-degree relatives [18]. Furthermore, in his classification of chronic depression, Akiskal [19] described a condition characterized by the presence of neurovegetative change and anhedonia as an antidepressant-responsive form of chronic depression. On the contrary, the conceptualization of AD referred to the classical definition given by Wernicke [20], subsequently elaborated by Jaspers [21], representing the inability of the self to imbue perceptions with emotional feelings. Although studies on patients with depersonalization disorder pointed out that AD is a homogenous construct [22,23], data on patients with mood disorders are still scanty. In classical psychiatric writings, AD can be connected with endogenous depression through the concept of loss of feelings or Gefühl der Gefühllosigkeit [24]. Its conceptualization needs to be differentiated from that of anhedonia because it goes beyond a general loss of affection or pleasure consisting of a number of different manifestations such as the loss of fear or disgust to situations previously avoided. Still, AD needs to be distinguished from the délire des negations, also known, in English literature, as Cotard syndrome [25]. In fact, although the “emotional anesthesia,” typical of AD, is regarded as an important feature of the Cotard syndrome [26], the subsequent analysis by Young and Leafhead [27] of original Cotard cases revealed a series of other commonly occurring symptoms such as self-deprecatory delusions, suicidal ideation, feelings of guilt, and denial of body parts. On this background, it is evident that both anhedonia and AD belong to depression, and a conceptual differentiation between them may have important practical implications not only in terms of a better definition of clinical endophenotypes of mood disorders for prognosis and response to treatments but also because it may allow further research on the neurobiology and neuropsychology of emotional processing. Therefore, this study is aimed to test the hypothesis that anhedonia and AD represent 2 different psychopathological dimensions in a large sample of patients with mood and anxiety disorders and to investigate their clinical correlates in patients with major depression and bipolar disorder (BD). 2. Methods 2.1. Participants A consecutive sample of adult outpatients presenting for treatment of mood and anxiety disorders at the Department

of Psychiatry in Pisa, Italy, from September 2006 to September 2007 were invited to participate in the study. Exclusion criteria were severe medical illnesses, neurological diseases, and inability to participate because of the severity of psychiatric symptoms. Eligible subjects provided written informed consent after receiving a complete description of the study and having an opportunity to ask question. The Ethics Committee of the Azienda Ospedaliera Universitaria of Pisa approved all recruitment and assessment procedures. 2.2. Instruments 2.2.1. Diagnostic assessment The diagnostic interviews consisted of the administration of the Structured Clinical Interview for DSM-IV Axis-I disorders [28] and a structured clinical interview consisting of 16 items derived from 2 instruments developed in the context of the Spectrum Project, namely, the Structured Clinical Interview for Mood Spectrum (SCI-MOODS) lifetime version [29] and the Structured Clinical Interview for Derealization-Depersonalization Spectrum (SCI-DER) lifetime version [30]. Cassano et al [3,31,32] observed that patients with psychiatric disorders may manifest a “spectrum” of associated clinical features not included in the criteria set. Some are “traitlike” symptoms that occur as subtle manifestations of an illness diathesi. Early onset of such symptoms may act to shape developing mental functions and change the personality. Failure to recognize and attend to residual and comorbid spectrum features in treating DSM-IV disorders may explain continued clinical impairment, even when core Axis I symptoms have been successfully treated [33]. To operationalize such spectrum model, researchers of the Spectrum Project developed a number of clinical instruments that proved to be valid and reliable (www.spectrum-project.net). All instruments have been developed with a similar structure to be used all together in a global dimensional assessment of psychopathology. In fact, all instruments explore the “presence” or “absence” of spectrum feature in the lifetime. Instrument versions exploring the last-month time frame are also available. 2.2.2. The Structured Clinical Interview for Derealization-Depersonalization Spectrum The SCI-DER was developed and validated at the Department of Psychiatry, Neurobiology, Pharmacology and Biotechnologies of the University of Pisa by experienced psychiatrists. It includes 49 items exploring presence or absence of lifetime symptoms of depersonalization organized into 4 domains: (1) derealization, (2) somatopsychic depersonalization, (3) autopsychic depersonalization, and (4) AD. Items responses are coded in a dichotomous way (yes/no), and total and domain scores are obtained by counting the number of positive answers. The SCI-DER proved to have sound psychometric properties: an excellent internal consistency (0.92), high test-retest reliability at 15 to 20 days (r = 0.88), and high convergent validity with respect to the Dissociative Experiences Scale (r = 0.74), and

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discriminant validity with respect to the Body Sensations Questionnaire (r = −0.18) [30].

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Table 2 Frequency of endorsement of items Item

2.2.3. The Structured Clinical Interview for Mood Spectrum The SCI-MOODS is focused on the presence of manic and depressive symptoms and consists of 161 items coded as present or absent for one or more periods of at least 3 to 5 days in the lifetime. It proved to have sound psychometric properties with a good internal consistency (0.79-0.92) and high test-retest reliability (r = 0.93-0.94) [29]. 2.3. Experimental procedures and statistical analysis In this study, we selected 8 items from the SCI-MOODS encompassing the definition of anhedonia and 8 items from the SCI-DER featuring AD to form a structured clinical interview of 16 items. All interviews were conducted by experienced research clinicians (qualified clinical psychologists) who were trained to the use of all study instruments at the Department of Psychiatry of the University of Pisa. An item response theory (IRT)-based factor analysis approach was carried out to analyze the structure of this 16item interview [34]. Although classical factor analysis makes use of information derived from pairwise correlations of items, IRT-based factor analysis makes use of all information in each patient's pattern of item responses, that is, item pairs, triplets, quadruplets, and so on, and is therefore called fullinformation factor analysis (FIFA). The FIFA operates directly on the patterns of positive/ negative responses without calculating correlation coefficients. In fact, this method fits a multidimensional item response model to the patterns in the sample data. The FIFA was conducted using promax rotation [35] to take into account the possible correlation between the 2 factors, as recommended by Fabrigar et al [36]. Bayes estimates of factor scores for all factors were obtained. Finally, Mann-Whitney test was used to compare factor scores in patients with BD and major depressive disorder (MDD). Spearman correlation coefficient was used to analyze associations between factor scores and age at onset of the disease in patients with BD and MDD. All statistical tests were 2-tailed with the significance level at .05. The IRT factor analysis was conducted using Table 1 The DSM-IV diagnoses in the clinical sample investigated (the total is more than 100% because of the presence of comorbidities) N = 258 Panic disorder Major depression BP II BP I Obsessive-Compulsive disorder Generalized anxiety disorder Social anxiety disorder Specific phobias Posttraumatic stress disorder Values are expressed as number (percentage).

140 (54.3) 85 (32.9) 48 (18.6) 43 (16.7) 30 (11.6) 16 (6.2) 5 (1.9) 3 (1.2) 2 (0.8)

M08 M21

M25 M14 M27 M15 D43 M23 D48 D47 M26 D46 D44 D49 D42 D45

Lost capacity to laugh, have fun, enjoy life Lost interest and pleasure in social life and to prefer spending most of time alone, withdrawing from family and friends Lost interest in hobbies or in playing games or sports Lost interest in how you looked Lost interest or pleasure in all or almost all the things usually enjoyed Nothing you put on looked or felt right Emotions were not in control Lost interest in romantic life Able to do things with amazing ease and spontaneity that would usually be difficult Not frightened at all in a situation that would normally find frightening or distressing Felt indifferent about everything that happened to you or your family Not feel any affection toward family or close friends What you were looking at seemed “flat” or “lifeless” Detached from memories of things that happened Turned off or detached from emotions Wept or laughed, not feel any emotions at all

78.3 74.8

72.9 66.7 66.7 64.3 60.9 58.5 51.2 40.7 38.0 34.9 31.4 31.4 25.6 22.5

TESTFACT (Version 4.0, 2003). All other analyses were conducted using the Statistical Package for Social Sciences (Version 15 for Windows, SPSS Inc Chicago, IL). 3. Results The study sample included 258 consecutive adult outpatients with mood and anxiety disorders; mean age was Table 3 Factor loadings derived from a 2-factor solution with promax rotation (factor 1 = anhedonia; factor 2 = AD) Item Lost interest in how you looked Nothing you put on looked or felt right Lost interest in hobbies or in playing games or sports Lost interest in romantic life Lost capacity to laugh, have fun, enjoy life Lost interest or pleasure in all or almost all the things usually enjoyed Lost interest and pleasure in social life and to prefer spending most of time alone, withdrawing from family and friends Emotions were not in control Wept or laughed, not feel any emotions at all Detached from memories of things that happened Turned off or detached from emotions Not feel any affection toward family or close friends Felt indifferent about everything that happened to you or your family What you were looking at seemed “flat” or “lifeless” Not frightened at all in a situation that would normally find frightening or distressing Able to do things with amazing ease and spontaneity that would usually be difficult

Factor 1 Factor 2 0.933 0.858 0.812 0.775 0.659 0.650

−0.220 −0.004 0.014 0.070 −0.083 0.171

0.599

0.142

0.353 −0.220 −0.187 −0.021 0.177 0.154

0.156 0.794 0.752 0.650 0.578 0.566

0.213 0.034

0.543 0.503

−0.028

0.366

Items with a factor loading greater than 0.40 are in boldface.

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43.5 ± 14.0 years; 60.5% were women; 51.9% were married, 6.2% separated or divorced, 38.4% never married; 46.9% had a high school diploma; and 52.3% were employed (Table 1). No subject refused to undertake and complete the interview, and the acceptability was extremely good. 3.1. Factor analysis The total number of items endorsed ranged from 0 to 16 (mean, 8.2; SD, 4.0). The frequency of endorsement of individual items is reported in Table 2. Items with the highest frequency in the sample include typical anhedonic symptoms such as lost capacity to laugh and lost interest in social life or in hobbies and sports. Using FIFA, 2 factors were extracted, accounting overall for 47.0% of the variance, the first factor accounting for 38.2% of the variance. The correlation between factors was 0.60 and therefore justifies the choice of promax rotation. After comparing 1-, 2-, and 3-factor solutions using the promax method, the 2-factor solution demonstrated superior model fit and parsimony. Factor loadings obtained using promax rotation are shown in Table 3, where items were organized by factors, then ordered by decreasing magnitude of loadings within factors. The first factor derived, anhedonia, featured loss of interest or pleasure in look (0.933), the way he or she looked (0.858), and hobbies (0.812). Factor 2, AD, included ‘not feeling any emotions at all’ (0.794), ‘detached from memories of things that happened’ (0.752), and detached from emotion (0.650). Two items had a factor loading less than 0.40. 3.2. Clinical correlates of anhedonia and AD factors in patients with mood disorders Anhedonia and AD factor scores were subsequently compared in patients with BD and MDD. There was no significant difference in sex, age of onset of the disease, and

Table 4 Demographic and clinical variables, comorbidity, AD, and anhedonia factor scores in patients with BD and MDD

Sex, females (%) Age, years ± SD Age of onset of the mood disorder, years ± SD Panic disorder (%) Obsessive-Compulsive disorder (%) Generalized anxiety disorder (%) Specific phobias (%) Anhedonia factor score, median (range) AD factor score, median (range) ⁎ P = .027.

BD (n = 91)

MDD (n = 85)

55 (60.4) 42.4 ± 12.6 28.2 ± 11.4

57 (67.1) 46.8 ± 13.8 31.2 ± 13.3

48 (52.7) 10 (11.0)

36 (42.4) 6 (7.1)

4 (4.4)

6 (7.1)

2 (2.2) 0.35 (−2.11 to 1.24)

1 (1.2) 0.14 (−2.14 to 1.05)

0.33⁎ (−1.24 to 2.17) −0.23 (−1.26 to 1.88)

Axis I comorbidity pattern between the 2 groups; however, patients with MDD were significantly older than those with BD (46.8 ± 13.8 vs 42.4 ± 12.6; t = 2.215, df = 174, P = .028) (Table 4). Patients with BD showed statistically significant higher AD factor scores than those with MDD (Z = 2.215, P = .027), whereas there was no between-groups difference in anhedonia scores (Z = 0.825, P = .411) (Table 4). In patients with BD, age of onset of the disease correlated with AD factor scores (ρ = −0.330, P = .001) but not with anhedonia factor scores (ρ = −0.097, P = .361).

4. Discussion In our study, based on a large data pool of subjects with mood and anxiety disorders and using 16 items derived from validated instruments, a 2-factor solution, accounting for 47% of variance, was identified with an IRT-based factor analysis approach. The factor analysis was conducted in patients with mood and anxiety disorders to take into account, in a lifetime perspective, not only full-blown symptoms but also subthreshold or isolated manifestations. Subsequently, clinical correlates of the 2 psychometrically derived dimensions were investigated among specific DSMIV categories, such as MDD and BD, in the light of a completing approach to psychopathology that included both categorical and dimensional constructs. Although specific clinical instruments have been developed for the assessment of anhedonia, such as the Scale for Physical and Social Anhedonia [37], the Pleasurable Activity Self-Rating Scale [38], or the Snaith-Hamilton Pleasure Scale [39], all of them were developed to investigate the current status or a limited time frame. On the contrary, the instrument used in this study investigates symptoms experienced in the lifetime. Our findings on the distinction between AD and anhedonia have both theoretical and practical implications. On a theoretical level, our data partly support neurobiological models speculating that these 2 dimensions underlie different brain networks. In fact, anhedonia is supposed to rely on the mesolimbic dopaminergic reward system [40] and AD on a functional sensory-limbic disconnection [41]. On a practical level, our data bear the possibility to identify specific clinical endophenotypes among patients with mood disorders. A number of authors identified anhedonia as an important component of depression [9,12,13], and a significant correlation was found with neuroticism, introversion, and morbid risk of depression in first-degree relatives [18]. Furthermore, previous authors suggested that anhedonia, suicidal ideation, and dexamethasone nonsuppression did identify a qualitatively distinct group, with anhedonia being strongly associated with suicidal ideation [42,43]. Conversely, literature on clinical correlates of AD in mood disorders is less apparent. However, the few published studies suggest that mood

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episodes with depersonalization symptoms are poorly responsive to electroconvulsive therapy [44,45] and sleep deprivation therapy [46]. In this light, it is interesting that AD scores, and not anhedonia scores, correlated with an early age at onset of the disease in BD subjects, further supporting the hypothesis that AD may represent a clinical index of disease severity [47]. Further studies investigating relationships with other selected indices of illness history (eg, number of depressive episodes, severity or duration of the depressive episodes) are warranted. The association between AD scores and BD diagnosis is particularly intriguing and fits nicely with other data suggesting that depersonalization symptoms are associated with bipolarity [48,49]. Although we stated that AD can be described in the context of endogenous depression, it has to be acknowledged that it belongs to the dissociative spectrum being related to depersonalization per se and, as such, to alterations of the self [23,47,50]. From an evolutionary point of view, depersonalization has been claimed to represent a vestigial brain response to life-threatening situations [51], but so far, this has been hypothesized for a particular subtype of depersonalization symptoms occurring in patients with anxiety disorders (eg, derealization, déjà vu phenomena, and so on), and nobody proposed that other depersonalization symptoms may occur also in mood disorders due to the same mechanism. In fact, strong mood disruptions and alterations that commonly occur in BD can, per se, disturb the stability of the self enough to induce depersonalization symptoms in general and AD in particular. In this regard, it is possible that the difference in AD scores, observed in our study (see Table 4), may be related to a higher number or more severe depressive episodes among patients with BD as compared to those with MDD. Nevertheless, it is tempting to speculate that AD may be associated with bipolarity. Further studies, replicating our findings, are needed, considering their possible clinical implications. In fact, BD still remains underdiagnosed and undertreated [52,53]. Our results need to be considered keeping in mind the following limitations. First, our results may not be representative of patients with mood disorders because our population represents a highly selected sample coming from a tertiary referral center. Second, the small sample size of patients with BD and MDD reduces the strength of our findings, and further studies are needed to replicate our findings in larger populations. Third, it has to be acknowledged that the clinical status may have a potential impact on the reliability of patients' report of lifetime signs and symptoms. However, data from our group indicate that the endorsement of lifetime symptoms with the SCI-MOODS is stable over time and is not sensitive to changes in clinical status [54]. No data are available about the SCI-DER so far. A number of issues warrant consideration in future research. The first relates to the possible role of AD as an outcome measure. In our experience, AD is less responsive than anhedonia to antidepressant drug treatment and may persist for a longer time even when other symptoms are

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remitted. These observations need to be further explored in studies of this area. Second, the identification of patients with specific profiles on multiple factors can be used to achieve a higher precision in brain imaging or neurobiological studies, not currently achieved using subjects with the same DSM-IV diagnosis. Finally, it is likely that a better psychopathological characterization of patients may inform on prognosis and specific treatment strategies.

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