discussion 3

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Journal of Affective Disorders

journal homepage: www.elsevier.com/locate/jad

Research paper

Are youths with disruptive mood dysregulation disorder different from youths with major depressive disorder or persistent depressive disorder? Xavier Benarousa,b,c, Johanne Renaudd,e, Jean Jacques Bretonf, David Cohenc,g, Réal Labellef,h,i,j, Jean-Marc Guiléa,b,e,⁎

a Child and Adolescent Psychopathology Services, Amiens University Hospital, Amiens, France b INSERM Unit U1105 Research Group for Analysis of the Multimodal Cerebral Function, University of Picardy Jules Verne (UPJV), Amiens, France c Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital, Sorbonne University, Paris, France dManulife Centre for Breakthroughs in Teen Depression and Suicide Prevention, Douglas Mental Health University Institute, McGill University, Montreal, Canada e Department of psychiatry, McGill University, Montreal, Canada fDepartment of psychiatry, University of Montreal, Montreal, Canada g CNRS UMR 7222, Institute for Intelligent Systems and Robotics, Sorbonne Universités, UPMC, Paris, France hDépartement de psychologie, Université du Québec à Montréal, Montréal, Canada i Centre de recherche, Hôpital en santé mentale Rivière-des-Prairies, CIUSSS du Nord-de-l’Île-de-Montréal, Canada j Centre for Research and Intervention on Suicide, Ethical Issues and End-of-life practices, (CRISE), Montreal, Canada

A R T I C L E I N F O

Keywords: Disruptive mood dysregulation disorder Major depressive disorder Persistent depressive disorder Suicidal behavior Adolescent Retrospective chart review

A B S T R A C T

Background: Although the disruptive mood dysregulation disorder (DMDD) was included in the depressive disorders (DD) section of the DSM-5, common and distinctive features between DMDD and the pre-existing DD (i.e., major depressive disorder, MDD, and persistent depressive disorder, PDD) received little scrutiny. Methods: Youths consecutively assessed as outpatients at two Canadian mood clinics over four years were included in the study (n = 163; mean age:13.4 ± 0.3; range:7–17). After controlling for inter-rater agreement, data were extracted from medical charts, using previously validated chart-review instruments. Results: Twenty-two percent of youths were diagnosed with DMDD (compared to 36% for MDD and 25% for PDD), with substantial overlap between the three disorders. Youths with DMDD were more likely to have a comorbid non-depressive psychiatric disorder – particularly attention deficit hyperactivity disorder, odds ratio (OR=3.9), disruptive, impulse-control and conduct disorder (OR=3.0) or trauma- and stressor-related disorder (OR=2.5). Youths with DMDD did not differ with regard to the level of global functioning, but reported more school and peer-relationship difficulties compared to MDD and/or PDD. The vulnerability factors associated with mood disorders (i.e., history of parental depression and adverse life events) were found at a comparable fre- quency across the three groups. Limitations: The retrospective design and the selection bias for mood disordered patients restricted the generalizability of the results. Conclusions: Youths with DMDD share several clinical features with youths with MDD and PDD. Further studies are required to determine the developmental trajec- tories and the benefits of expanding pharmacotherapy for DD to DMDD.

1. Introduction

Over the last two decades, the diagnosis and treatment of children presenting with severe and chronic irritability has become a challenge within the context of the pediatric bipolar controversy (Masi et al., 2015; Roy et al., 2014; Consoli and Cohen, 2013; Tourian et al., 2015). On the basis of studies of youths with severe mood dysregulation (SMD), a clinical presentation characterized by persisting irritability

and recurrent temper outbursts, the disruptive mood dysregulation disorder (DMDD) was included as a new diagnostic entity in the de- pressive disorders (DD) section of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) (American Psychiatric Association 2013). The DMDD is characterized by persistent irritable mood and, severe (i.e. out of proportion in intensity or duration) and frequent (i.e. three or more times per week) temper outbursts.

The discriminant validity of DMDD and its inclusion among DD

https://doi.org/10.1016/j.jad.2020.01.020 Received 12 March 2019; Received in revised form 27 November 2019; Accepted 5 January 2020

⁎ Corresponding author at: Child and Adolescent Psychiatry Services, Amiens University Hospital, Amiens, France, CHU Amiens-Picardie, Site Sud, F-80054 Amiens, France.

E-mail address: [email protected] (J.-M. Guilé).

Journal of Affective Disorders 265 (2020) 207–215

Available online 08 January 2020 0165-0327/ © 2020 Published by Elsevier B.V.

T

have been, and still are, controversial issues (Roy et al., 2014; Stringaris et al., 2017). The inclusion of DMDD in the DD section of the DSM-5 was supported by longitudinal studies showing that chronic ir- ritability in childhood led to internalizing disorders in adolescence and early adulthood, in particular anxiety and depressive disorders (Brotman et al., 2006; Stringaris et al., 2009; Stringaris et al., 2010; Leibenluft E. Severe Mood Dysregulation 2011; Vidal-Ribas et al., 2016). The relationship between childhood irritability and depression in adolescence was also supported by genetic and family studies (Cross- Disorder Group of the Psychiatric Genomics Consortium 2013; Propper et al., 2017; Krieger et al., 2013; Wiggins et al., 2018; Brotman et al., 2007; Stringaris et al., 2012; Savage et al., 2015).

The delimitation of DMDD from other psychiatric disorders, and, in particular mood disorders, is an essential step towards the establish- ment of its diagnostic validity (Robins and Guze, 1970). To date, the literature has mainly focused on the distinction between DMDD (and the research clinical entity of SMD) and bipolar disorder (BD) (Stringaris et al., 2010). In contrast, the validity of DMDD has not been questioned against DD, i.e., major depressive disorder (MDD) and persistent depressive disorder (PDD). PDD differs from MDD with re- spect to the severity and duration of depressive symptoms. PDD is a chronic DD whereas MDD is regarded as mostly, but not exclusively, episodic. Cumulative findings showed that the chronic versus episodic course of mood symptoms is a key clinical feature with distinctive clinical correlates (Masi et al., 2006) and outcome in adulthood (Leibenluft et al., 2006). DMDD differs from DD, both PDD and MDD, with respect to the presence of temper outbursts and the nature of mood symptoms. Findings from the prospective population-based Great Smoky Mountains Study (Stringaris et al., 2013) showed that depressed mood was the most common cardinal mood symptom in youth meeting criteria for DD. On the contrary, irritable mood alone was rare (5.7%). Given that no study has questioned DMDD against MDD or PDD, the differences between MDD, PDD and DMDD (in terms of clinical corre- lates, natural course, and vulnerability factors) have yet to be char- acterized. The present study aimed to address these issues.

The first objective of the present study was to determine the fre- quency of DMDD (compared to MDD and PDD) in a clinical outpatient sample. The frequency of DMDD is expected to be similar to the values reported in outpatient samples (22–31%) (Margulies et al., 2012; Axelson et al., 2012; Freeman et al., 2016; Tufan et al., 2016). The extent of overlap between DMDD, MDD and PDD would help to docu- ment the validity of the diagnosis of DMDD. Indeed, if DMDD is a distinct, valid clinical entity, its overlap with MDD and/or PDD should be moderate - or at least no larger than for the two other disorders.

The study's second objective was to compare the clinical char- acteristics of youths with DMDD, MDD and PDD. We hypothesized that the comorbidity rate would be higher for DMDD than for the two other disorders. This would be in line with previous studies showing a high rate of comorbidity in children and adolescents with DMDD compared to other psychiatric disorders (Margulies et al., 2012; Axelson et al., 2012; Freeman et al., 2016; Tufan et al., 2016; Dougherty et al., 2014; Axelson, 2013; Stringaris and Taylor, 2015; Copeland et al., 2013). This would also be consistent with the assumption that irritability, the core symptom in DMDD, is located at the interface between internalizing disorders and externalizing disorders (Stringaris and Taylor, 2015).

The study's third objective was to compare the impairments re- spectively associated with DMDD, MDD and PDD. We expected that youths with DMDD would present a range of peer-relationship diffi- culties that went beyond aggressive behavior. Several dysfunctions in social information processing have been reported in youths with chronic irritability; this exposes them to a greater risk of experiencing repeated interpersonal difficulties (Leibenluft E. Severe Mood Dysregulation 2011; Vidal-Ribas et al., 2016; Vidal-Ribas et al., 2018). Based on preliminary findings, we would also expect school functioning to be more impaired in youths with DMDD than in youths with MDD or PDD (Dougherty et al., 2014; Copeland et al., 2013).

Lastly, the study's fourth objective was to compare the vulnerability factors profile for mood disorders in youths with DMDD, MDD and PDD. The focus was placed on vulnerability factors consistently associated with DD in children and adolescents, i.e., a first-degree family history of depression, a history of adverse life events and an impaired develop- mental history (Thapar et al., 2012).

2. Methods

2.1. Participants

Data were retrospectively reviewed after their extraction from the medical records of youths referred to the two mood disorder outpatient clinics in Montreal (Canada) between November 2006 and December 2010. The recruitment sites for French-speaking and English-speaking youths were respectively the Rivière des Prairies Hospital (RPH) and the Douglas Mental Health University Institute (DMHU). The main in- clusion criteria were age between 7 and 17, and admission to one of the two outpatient clinics following a standardized diagnostic evaluation by a multidisciplinary team (including a child psychiatrist). A total of 163 consecutive participants were assessed (114 at RPH and 49 at DMHU) during the study period. The study population comprised 65 males (40%) and 98 females (60%), and the mean± standard deviation (range) age was 13.4 ± 0.3 (7‒17).

2.2. Setting and study design

Clinical and sociodemographic data were gathered using a chart review instrument that had previously been validated in a retrospective study of adolescent outpatients with DD (Breton et al., 2012; Guile et al., 2016; LeBoeuf et al., 2017). The instrument recorded all the clinical data noted by healthcare professionals (clinicians, social workers and nurses) in the patient's medical file. All information per- taining to a participant's identity was removed. The inter-rater agree- ment (κ = 0.80) had previously been measured at each site, using a sample of ten charts. Data on sociodemographic characteristics, family and personal medical histories, DSM diagnoses, symptoms, and treat- ment were extracted using the instrument. In the medical records, the psychiatric diagnoses had been defined according to the DSM-IV-TR criteria and categories. In the current analysis, the psychiatric diag- noses were presented with respect to the DSM-5 criteria and categories. At both recruitment sites, the routine diagnostic work-up encompassed several standardized evaluations including the Schedule for Affective Disorders and Schizophrenia for School-Age Children (K-SADS-PL) (Kaufman et al., 1997) and the Children-Global Assessment Scale (C- GAS) (Shaffer et al., 1983). In accordance with the ethics regulatory framework enforced in the province of Québec (Canada), access to medical files was authorized by the Director of Professional Services at each of the two investigating centers.

2.3. Measurements

2.3.1. Psychiatric diagnoses The K-SADS-PL was completed as part of each patient's routine

clinical assessment at DMHU and RPH. The parents were the informants in the present study. The K-SADS-PL’ internal validity (inter-rater re- liability: 93–100%; test-retest reliability: 0.74–0.90) and external va- lidity are excellent. Clinical data relative to psychiatric diagnoses were extracted using the chart review instrument. Apart from the removal of the bereavement exclusion criteria, the diagnostic criteria for MDD in DSM-5 (notably the presence of symptoms for at least two weeks) are the same as those in DSM-IV-TR. The diagnosis of PDD was introduced in the DSM-5 as a consolidation of the previously defined DSM-IV-TR category of dysthymia and the chronic subtype of MDD. All participants meeting criteria for dysthymia have been identified as PDD. None of the study participants met the criteria for chronic subtype of MDD.

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With respect to the DMDD diagnosis, symptoms reported in the patient's medical file were compared with the DSM-5 criteria for DMDD. Data were abstracted using an additional chart review instru- ment based on the criteria for temper dysregulation disorder with dysphoria - a research entity developed by the DSM-5 Task Force prior to the publication of the final criteria for DMDD (Leibenluft E. Severe Mood Dysregulation 2011; American Psychiatric Association Taskforce DV 2010) . Each criterion was scored as present, absent or unknown. The diagnostic algorithm is provided in the Supplementary Material, and follows the international guidelines (Table S1) (American Psychiatric Association Taskforce DV 2010). In particular, DMDD was endorsed only if the patient met the criteria for duration, cross-domain impair- ment, and age of onset, with the exclusion criteria rule for bipolar disorder. The psychometric properties of this diagnostic instrument for DMDD have previously been explored in another sample of 12- to 15- year-old outpatients (n= 192; Cronbach's α for internal validity: 0.90; κ for test-retest reliability: 0.87) (Boudjerida et al., 2018).

2.3.2. Suicidal behavior and substance use Suicidal behavior was documented by rating a set of four items:

“prior suicidal ideation”, “a single prior suicide attempt”, “multiple prior suicide attempts”, and “prior self-aggressive behavior”. The Columbia- Suicide Severity Rating Scale (C-SSRS) (Posner et al., 2007) was com- pleted for the study participants at the DMHU clinic. The C-SSRS as- sesses various forms of suicidal behaviors (active suicidal ideation, in- terrupted suicide attempts, and aborted suicide attempts), and non- suicidal self-injuries.

Substance use was documented using a set of five items: “prior use of a substance”, “regular alcohol use”, “regular alcohol use before the age of 12″, “regular tobacco use”, and “regular tobacco use before the age of 12″. In the study sample from DMHU, the DEP-ADO questionnaire (Germain et al., 2007) was additionally used to document substance use in the previous 12 months. The screening question was “During the last twelve months, how often have you [has X] used one of the following sub- stances: alcohol, cannabis, cocaine, inhalant/solvent, stimulant, halluci- nogen, or heroin”; examples and trivial names were provided for each substance.

2.3.3. Functional impairment The level of global functioning was evaluated using the Children-

Global Assessment Scale (C-GAS) (Shaffer et al., 1983) on the basis of the multidisciplinary evaluation at the first medical visit. Peer-re- lationship problems were assessed by the clinician using an eight-item checklist used in chart reviews for the assessment of social functioning in youths with DD (Breton et al., 2012; Guile et al., 2016; LeBoeuf et al., 2017). The instrument whose reliability has been previously assessed (Breton et al., 2012), regroups the following items: physical and ag- gressive behaviors, stealing goods from other youths, passive and active social withdrawal, feeling of being rejected by other youths, victim of physical or verbal aggression. School impairments were assessed using the school reports annexed to the medical file with regard to the fol- lowing domains: prior grade repetition, reported learning difficulties, repeated unjustified school absence.

2.3.4. Vulnerability factors A modified version of the Family History Screen (Weissman et al.,

2000) was used to retrospectively collect information on the psychiatric history of the participants’ first- and second-degree relatives. This in- cluded the history of paternal and maternal depression, which is the most well-recognized risk factor for children and adolescent depression (Thapar et al., 2012). Adverse childhood experiences (ACE) were as- sessed using all available data, with respect to a set of ten items from the Adverse Childhood Experience Questionnaire (Anda et al., 2010) A major ACE was defined as an episode of physical and/or sexual and/or emotional abuse and/or a severe form of emotional and/or physical neglect (Anda et al., 2010). Data from administrative sources (e.g. a

history of placement in foster care) were also collected following the method used in previous chart-review studies for pediatric mood dis- orders (Garno et al., 2005; Benarous et al., 2017a). The developmental history was explored regarding four domains: a history of complicated pregnancy, a history of delayed psychomotor development, the pre- sence of an associated neurological disorder, and a history of head trauma.

2.4. Statistical analyses

Considering the small sample size and the non-Gaussian data dis- tribution, non-parametric Kruskal-Wallis tests were used to compare three groups: (i) youths with DMDD (and, in some cases, a concomitant DD), (ii) youths with MDD only (i.e., without DMDD and/or PDD), and (iii) youths with PDD only (i.e., without DMDD and/or MDD). First, we aimed at increasing the homogeneity of the control groups and thus raise the study's statistical power. Second, in order to increase external validity, we wanted to form the largest possible and most representative clinical sample of youths with DMDD. In order to facilitate the inter- pretation of our findings with respect to the previous studies (Margulies et al., 2012; Axelson et al., 2012; Freeman et al., 2016; Tufan et al., 2016), we compared the DMDD group with the rest of the sample (“non-DMDD youths”) (studies detailed in Table S2). The groups were compared using Pearson's chi-squared test or Fisher's exact test for categorical variables (e.g., DSM-5 diagnoses), and Student's test or a Mann-Whitney test for continuous variables (e.g., age). Similar analyses were performed for the study's third and fourth objectives. The results were not corrected for multiple comparisons; we considered that in the context of an exploratory analysis, the type II error outweighed the type I error. All statistical analyses were performed with STATASE software (version 12). The threshold for statistical significance was set to p < .05. All analyses were replicated with (i) a more homogeneous DMDD group (i.e., after the exclusion of youths with associated MDD and/or PDD), and (ii) a DMDD group without associated Attention Deficit with/out Hyperactivity Disorder (ADHD) (Table S3).

3. Results

3.1. Objective 1. Frequency of DMDD and overlap with MDD and/or PDD

Thirty-six youths (22%) met the criteria for DMDD (Table 1). The frequencies of MDD and PDD were respectively 36% and 25%. The two sites did not differ significantly (p= .191) with regard to the frequency of DMDD. Thirty-six percent of the youths with DMDD were also di- agnosed with a DD (MDD n = 7, PDD n = 6), but none met the di- agnostic criteria for all three disorders (Fig. 1).

3.2. Objective 2. Clinical characteristics of youths with DMDD, MDD and PDD

Youths with DMDD were an average of 3.3 years younger than those with MDD and 2.5 years younger than those with PDD. The proportion of boys was significantly higher in the DMDD group than in the other two groups.

The comorbidity profiles of youths with DMDD and youths with other DD are summarized in Table 2. All the youths with DMDD had at least one other comorbid DSM-5 diagnosis. The number of comorbid- ities was significantly higher among youths with DMDD than among youths with MDD or PDD. Compared with youths with PDD or MDD, youths with DMDD were more likely to have concurrent trauma- and stressor-related disorders (odds ratio (OR)=2.5, p=.004), ADHD (OR=3.9, p<.001) or disruptive, impulse-control and conduct dis- orders (DICCD) (OR=3.0, p=.006). The frequency of anxiety disorders was highest in the PDD group and lowest in the MDD group. The DMDD, MDD or PDD groups did not differ significantly with regard to the frequency of substance use (see Fig. 3), learning disorders or other

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psychiatric disorders. The proportion of youths with suicidal ideation was significantly

lower for the youths with DMDD than for youths with MDD or PDD

(Fig. 2). However, the frequencies of suicide attempts, multiple suicide attempts, and non-suicidal self-injuries were similar in the three groups. After examining the C-SSRS data for the 14 youths with DMDD from the DMHU site, we found that 8 participants had made a suicide attempt (hanging in one case, wrist-cutting in three cases, and another method in four cases). Six of the 8 suicide attempts were impulsive. Only one participant had made multiple suicide attempts.

3.3. Objective 3. Impairments associated with DMDD, MDD and/or PDD

The C-GAS score, as measured during the first medical visit, did not statistically differ between the three groups (Table 3). However, youths with DMDD reported more learning difficulties and a more frequent history of grade repetition, relative to youths with MDD or PDD. Peer relationships were significantly more impaired in youths with DMDD compared to youths with MDD or PDD. Youths with DMDD were 3–4 times more likely to display physically or verbally aggressive behavior; they were also more likely to have been victims of verbal and physical aggression.

3.4. Objective 4. Vulnerability factors associated with DMDD, MDD and/or PDD

Exposure to parental mental illness was more frequent in youths with MDD than in youths with DMDD or PDD (Table 4). However, no statistically significant difference was found between the three groups with regard to the family history of psychiatric diagnoses, including depression and substance use.

The proportion of major ACE and the frequency of foster care pla- cement did not differ between the DMDD, MDD and PDD groups.

Youths with DMDD were significantly more likely to have a history of complicated pregnancy than youths with MDD or PDD, but the as- sociation was no longer statistically significant after youths with DMDD

Table 1 Frequency of psychiatric disorders among recruitment sites.

RPH (n = 114)

DMHU (n = 49)

Total (N = 163)

Internalizing disorders Mood disorders MDD 40 (35%) 19 (39%) 59 (36%) PDD 30 (26%) 10 (20%) 40 (25%) DMDD 22 (19%) 14 (29%) 36 (22%) BD-I/II 12 (11%) 1 (2%) 13 (8%)

Anxiety disorders 18 (16%) 21 (43%) 39 (24%) Trauma- and stressor- related disorders a

13 (11%) 14 (29%) 27 (17%)

Externalizing disorders ADHD 28 (25%) 16 (33%) 44 (30%) DICCD 34 (30%) 9 (18%) 43 (26%) Substance use disorder 7 (6%) 4 (8%) 11 (7%)

Psychotic and developmental disorder Schizophrenic disorder and other psychotic disorder

1 (1%) 0 1 (1%)

Learning disorder 10 (9%) 11 (22%) 21 (13%) Other psychiatric disorders b 8 (7%) 7 (14%) 15 (9%)

Note. RPH= Mood Disorders Clinic at the Rivière-des-Prairies Hospital; DMHU= Program of DD Pediatric section of the Douglas Mental Health University Institute; MDD= major depressive disorder; PDD= persistent de- pressive disorder; DMDD= disruptive mood dysregulation disorder; ADHD= attention deficit hyperactivity disorder; BD= bipolar disorder type 1 and type 2; DICCD= disruptive, impulse-control and conduct disorders.

a The category “Trauma- and Stressor-Related Disorders” encompasses ad- justment disorder, acute stress disorder and post-traumatic stress disorder.

b The category “Other psychiatric disorders” encompasses sleep disorder, tics and Tourette syndrome, obsessive compulsive disorder, eating disorder.

Fig. 1. Overlap between disruptive mood dysregulation disorder, major depressive disorder and persistent depressive disorder.

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and ADHD were excluded from the analysis (Table S3). No difference was observed regarding the psychomotor development and the asso- ciation with a neurological disorder.

4. Discussion

4.1. Interpretation

Regarding the study's first objective, the frequency of DMDD ob- served (22%) was slightly lower than that reported for two other out- patient studies using retrospective diagnoses (see Table S2) (Axelson et al., 2012; Freeman et al., 2016). Twenty-six to 31% of the 706 children aged 6–12 years in the Longitudinal Assessment of Manic Symptoms study met the criteria for DMDD (Axelson et al., 2012). Among the 597 children and adolescents (ages 6–18) treated at a community mental health center in the US, 31% were diagnosed with

DMDD (Freeman et al., 2016). The frequencies observed in child psy- chiatry facilities clearly contrast with the relatively low prevalence estimate of 1% in the general population (Stringaris et al., 2018). The disparity in the reported frequencies may result from disparities in countries’ prevalence rates, sampling bias, and more likely, differences in the diagnostic procedures, our study being uniquely based on the DMDD algorithm of the DSM-5.

The degree of overlap between DMDD and DD was substantial (36%), but comparable to the overlap observed with each other group: 30% with PDD and 22% with MDD.

Regarding our second objective, youths with DMDD were younger and more likely to be male than youths with either PDD or MDD. This higher proportion of males among youths with DMDD has been con- sistently reported in previous studies (Margulies et al., 2012; Axelson et al., 2012; Freeman et al., 2016; Tufan et al., 2016; Dougherty et al., 2014; Axelson, 2013; Stringaris and Taylor, 2015;

Table 2 Clinical characteristics of children and adolescents with DMDD, MDD, and PDD.

DMDD (n = 36) MDD only (n = 46) PDD only(n = 28) Comparisons between the three groupsd

Non DMDD (n = 127)

Comparisons DMDD vs. non-DMDDe

Socio-demographic features Gender, male, n (%) 22 (61%) 13 (28%) 11 (39%) p = .01 43 (34%) p < .01 Age (years) (mean±SD) 11.5 ± 3.4 14.8 ± 2.53 14.0 ± 2.93 p < .01 13.9 ± 2.91 p < .01 Socio economic difficulties 4 (11%) 2 (4%) 12 (43%) p < .01 24 (19%) p = .274

Number of psychiatric disorders 2.5 ± 0.6 1.9 ± 0.8 2.2 ± 0.7 p < .01 2.1 ± 0.8 p < .01 DSM-5 associated psychiatric disorders Internalizing disorders Anxiety disorders 9 (25%) 5 (11%) 11 (39%) p = .016 30 (24%) p = .829 Trauma- and stressor- related disorders a

10 (28%) 0 1 (4%) p < .01 17 (13%) p = .040

Externalizing disorders ADHD 18 (50%) 5 (11%) 4 (14%) p < .01 26 (21%) p < .01 DICCD 16 (44%) 11 (24%) 3 (11%) p = .009 27 (21%) p = .005 Substance use disorder 3 (8%) 2 (4%) 1 (4%) p = .651 8 (6%) p = .668

Developmental and other disorders b

Learning disorder 7 (19%) 5 (11%) 3 (11%) p = .472 14 (11%) p = .257 Other psychiatric disorders c

4 (11%) 4 (9%) 3 (11%) p = .927 11 (9%) p = .654

Note. Statistically significant results are presented in bold. ADHD= attention deficit hyperactivity disorder; DICCD= disruptive, impulse-control and conduct disorders.

a The category “Trauma- and Stressor-Related Disorders” encompasses adjustment disorder, acute stress disorder and post-traumatic stress disorder. b Nobody presented a schizophrenic disorder or other psychotic disorder among youths with DMDD, MDD or PDD. c The category “Other psychiatric disorder” encompasses sleep disorder, tics and Tourette syndrome, obsessive compulsive disorder, eating disorder. d Kruskal-Wallis test. e Fisher's Exact test, except for “number of psychiatric diagnosed” where Mann-Whitney U-test was used.

Fig. 2. Suicidal behaviors among youth with DMDD, MDD without DMDD/PDD, and PDD without DMDD/MDD.

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Copeland et al., 2013; Copeland et al., 2014). The higher comorbidity, observed in our sample, with externalizing disorders associated with a predominantly male sex ratio (Breton et al., 1999), could have con- tribute to this finding. Of note, the sex ratio observed with DMDD differs from the more balanced sex ratio reported in depressed pre- pubertal children (Angold and Rutter, 1992). The high comorbidity rate among youths with DMDD reported in the present study is in line with all the prior studies, in which other psychiatric disorders were observed in between 60% and 92% of outpatients with DMDD (Margulies et al., 2012; Axelson et al., 2012; Freeman et al., 2016; Tufan et al., 2016; Dougherty et al., 2014; Axelson, 2013; Stringaris and Taylor, 2015; Copeland et al., 2013). In our sample, ADHD and DICCD were the most frequently associated diagnoses in youths with DMDD. Most interest- ingly, youths with DMDD were 2.5 times more likely to have an asso- ciated trauma-and stressor-related disorder, compared to youths

without DMDD. To our knowledge this is the first study reporting a positive association between DMDD and trauma-related disorders (Table S2). Albeit preliminary, this finding brings additional support to the postulated relationship between the exposure to chronic stress/re- peated trauma and chronic mood dysregulation (Dvir et al., 2014).

In the present study, youths with DMDD presented with a lower frequency of suicidal ideation than the other two groups. In keeping with the relationship between suicidal behavior and the DMDD core symptom of irritability, and as previously discussed (Benarous et al., 2018), suicide attempts might result from the intermixture of covert suicidal ideation and a temporary increase in irritability caused by in- tercurrent triggering stressors. This model described in literature (Benarous et al., 2018; Stringaris and Vidal-Ribas, 2019; Orri et al., 2018) is further supported by our data as youths with DMDD mostly reported suicidal attempts as unplanned and impulsive.

Fig. 3. Substance use among youth with DMDD, MDD without DMDD/PDD, and PDD without DMDD/MDD.

Table 3 Functional impairment associated with DMDD, MDD, and PDD.

DMDD (n = 36) MDD only (n = 46)

PDD only(n = 28) Comparisons between the three groupsb

Non DMDD (n = 127)

Comparisons DMDD vs. non-DMDDc

C-GAS: Mild or severe functional impairment a

10 (28%) 23 (50%) 9 (32%) p = .092 58 (45%) p = .064

School achievement Prior grade repetition 14 (39%) 6 (15%) 5 (18%) p = .030 23 (20%) p = .044 Reported learning difficulties 9 (25%) 2 (4%) 4 (14%) p = .025 15 (12%) p = .049 Repeated school absence 7 (19%) 9 (20%) 9 (32%) p = .394 26 (21%) p = .892

Peer relationship problems 1. Physical aggressive behaviors 14 (39%) 5 (11%) 2 (7%) p < .01 14 (11%) p < .01 2. Verbal aggressive behaviors 17 (47%) 5 (11%) 4 (14%) p < .01 19 (15%) p < .01 3. Stealing goods from other youths

5 (14%) 5 (11%) 2 (7%) p = .698 10 (8%) p = .326

4. Passive social withdrawal 20 (56%) 26 (56%) 15 (54%) p = .971 69 (54%) p = .956 5. Active social avoidance 3 (8%) 2 (4%) 1 (4%) p = .651 5 (4%) p = .376 6. Rejected by other youths 13 (36%) 9 (20%) 8 (29%) p = .249 46 (35%) p = .960 7. Victim of physical aggression 5(14%) 3 (7%) 1 (4%) p = .205 5 (4%) p = .026 8. Victim of verbal aggression 14 (39%) 10 (22%) 5 (18%) p = .109 28 (22%) p = .037 Mean total score (0 to 8) 2.4 ± 1.6 1.3 ± 1.2 1.3 ± 1.2 p < .001 1.5 ± 1.2 p < .01

Note. Statistically significant results are presented in bold. a Mild or severe functional impairment is defined as a C-GAS score strictly above 60. b Kruskal-Wallis test. c Fisher's Exact test.

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With respect to the study's third objective, unlike prior studies (Dougherty et al., 2014; Copeland et al., 2013), no significant difference was observed between the three groups relative to the measure of global functioning (C-GAS score). However, several other findings mi- tigated this overall absence of association. First, youths with DMDD presented more school difficulties (leaning difficulties and a more fre- quent history of grade repetition) and peer-relationship problems compared to youths with MDD or PDD. The poor levels of school achievement of youths with DMDD was in line with previous commu- nity studies (Dougherty et al., 2014; Copeland et al., 2013). Copeland et al. (2013) reported that the frequency of recent school suspension was higher among youths with DMDD than among psychiatric case- controls (Copeland et al., 2013). Dougherty et al. (2014) (Dougherty et al., 2014) in turn, noted that youths with DMDD were more likely than their counterparts to require remedial education. Further studies are needed to determine whether the association be- tween DMDD and learning difficulties can be explained by the presence of perinatal risk factors and other developmental difficulties. Our data support this hypothesis because the relationship was no longer statis- tically significant after youths with ADHD had been excluded from the analysis (Table S3).

Second, the positive association between DMDD and aggressive behavior might be seen as somewhat inevitable, since aggressive reac- tions can be seen as a consequence of irritability. However, youths with DMDD were more likely to be victims of aggressive behavior by peers than youths without DMDD; this finding is in line with earlier reports on youths displaying reactive aggression (Geoffroy et al., 2018). Only longitudinal studies might be able to determine the interplay between victimization by peers, reactive aggression, and mood symptoms in chronically irritable youths. Among youths with chronic irritability, it has been noted neurocognitive impairments (e.g. emotional recognition difficulties), which were involved in the daily expression of social skills (Vidal-Ribas et al., 2018; Stoddard et al., 2015) . They would be worth studying to better understand peer-relationship difficulties in youths with DMDD, in comparison to MDD and PDD.

With respect to the last objective relative to vulnerability factors, no statistically significant difference was found between the three groups with regard to the family history of psychiatric diagnoses. This meant that the well-documented vulnerability factor for childhood depression, i.e., the history of parental depression, was observed at a similar rate among the three groups. The association between a history of compli- cated pregnancy and DMDD is probably partly mediated by the pre- sence of developmental cognitive impairments, since the association

was no longer significant after the exclusion of youths with DMDD and ADHD (Table S3).

On should remain cautious with regard to these preliminary find- ings. First, reporting no differences does not mean that the role of the vulnerability factor is comparable across the three groups. Second, in- formation on the vulnerability factors resulted from a cross-sectional study design rather than a prospective longitudinal study. We can only conclude that on a small sample of help-seeking outpatients, no sig- nificant difference was observed with respect to the youth's profile of environmental vulnerability factors associated with mood disorders between DMDD, MDD, and PDD.

4.2. Strength and limitations

The results of this study should be interpreted in the context of its limitations. Firstly, the study suffered from retrospective bias and a small number of patients in the study groups - despite the four-year recruitment period. The study's statistical power was reduced by the substantial number of variables, and the small sample size also pre- cluded the use of multivariate analysis. It will be important to confirm that the observed differences between the DMDD, MDD and PDD groups do not reflect sociodemographic features. Secondly, the eva- luation of psychosocial risk factors (such as ACE) may be prone to recall bias. To limit the potential bias, we measured the data's validity against official records (i.e. administrative data from child protection agencies). Thirdly, the lack of a control group without psychiatric disorders makes it more difficult to interpret intergroup differences between groups. To facilitate comparisons with previous studies, we compared DMDD and non-DMDD subsets. Fourthly, the study sample comprised outpatients consulting at specialist mood disorders clinics in a large urban area. This might account for the high observed prevalence of mood disorders and the relative paucity of other conditions for which there are specific care pathways (e.g. severe developmental disorders). Our results could only be generalized to other clinics with similar patient profiles.

The study also had a number of strengths: (i) the use of a well- validated, DSM-5-based instrument for the clinical diagnosis of DMDD, (ii) our comparison of mood disorder groups addresses important issues in how DMDD can be discriminated from pre-existing DD diagnoses in clinical practice, and (iii) some environmental risk factors (such as the developmental history and ACE) have never been investigated in DMDD.

Table 4 Vulnerability factors associated with DMDD, MDD, and PDD.

DMDD (n = 36)

MDD only (n = 46)

PDD only(n = 28) Comparisons between the three groupsa

Non DMDD (n = 127)

Comparisons DMDD vs. non- DMDDb

Family psychiatric history Maternal depression 11 (31%) 21 (46%) 8 (29%) p = .231 54 (43%) p = .198 Paternal depression 6 (17%) 13 (28%) 4 (14%) p = .273 24 (19%) p = .762

Stressful life events History of major ACEs 14 (39%) 15 (33%) 16 (57%) p = .111 56 (44%) p = .703 Exposure to parental substance abuse

11 (31%) 8 (17%) 2 (7%) p = .057 23 (18%) p = .110

Exposure to parental mental illness

19 (53%) 33 (72%) 12 (43%) p = .036 83 (64%) p = .249

Foster care placement 5 (14%) 4 (9%) 1 (3%) p = .367 7 (19%) p = .326 Developmental history Complicated pregnancy 8 (22%) 2 (4%) 2 (7%) p = .027 7 (6%) p < .01 Delay in psychomotor development

2 (6%) 0 2 (7%) p = .217 4 (3%) p = .614

Neurological disorder associated

5 (14%) 4 (9%) 4 (14%) p = .696 12 (10%) p = .536

Note. Statistically significant results are presented in bold. a Kruskal-Wallis test. b Fisher's Exact test.

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4.3. Clinical and research implications

In this study, we aimed at documenting the common and distinctive features of DMDD, MDD, and PDD. As mentioned in the introduction, there is still an ongoing debate about the best diagnostic approach for youths with chronic irritability, i.e. whether adding a new specifier for youths with oppositional defiant disorder (ODD) or subtyping DD with a new diagnostic entity as proposed with the DSM-5 (Roy et al., 2014; Stringaris et al., 2017). Therefore, following Occam's razor principle, it is mandatory to compare DMDD with preexisting DD diagnostic cate- gories, i.e. MDD and PDD, to ensure that the new clinical entity is not a more fashionable label for youths with chronic depression, i.e. PDD. In keeping with the aforementioned debate, this study has several im- plications.

First, DMDD could be discriminated from MDD and PDD. Of the 36 youths with DMDD, only six met the criteria for PDD. This is in line with the assumption that youths with chronic irritability do not fit prior DD diagnostic categories, and therefore deserve a more specific DD diagnostic category. In contrast, the high comorbidity rate consistently reported for DMDD (Margulies et al., 2012; Axelson et al., 2012; Freeman et al., 2016; Tufan et al., 2016)., may dismiss the claim for specificity. However, in this study and all the prior studies, the DSM-5 non-dual diagnosis criterium for ODD was not applied, resulting in an overestimation of the comorbidity rate of DMDD with externalizing disorders. In addition, youths with DMDD presented a more mixed clinical presentation with mood and developmental disturbances com- ponents (i.e., younger age, predominantly male sex ratio, history of complicated pregnancy, persisting peer-relationship and school diffi- culties) compared to youths with MDD and/or PDD. This clinical pre- sentation with an admixture of mood and developmental disturbances was only partially mediated by the association with ADHD (Table S3). Therefore, youths presenting with DMDD should be carefully assessed for neurodevelopmental disorders.

Second, from a research standpoint, the aforementioned neurocog- nitive characteristics could be seen as promising mediators between childhood irritability and later depression (Vidal-Ribas et al., 2018). The relation between chronic irritability in childhood and, depression in adolescence and adulthood has been well demonstrated, in particular on the basis of longitudinal studies (Brotman et al., 2006; Stringaris et al., 2009; Stringaris et al., 2010; Leibenluft E. Severe Mood Dysregulation 2011; Vidal-Ribas et al., 2016; Whelan et al., 2013). In a meta-analysis, Vidal-Ribas et al. (2016) reported a positive and in- dependent relation between chronic irritability in childhood on the one hand and on the other hand, depression in adolescence and adulthood (OR=1.80) (Vidal-Ribas et al., 2016). Consequently, search for common pathophysiological underpinnings is under way. Families studies unveiled an association between childhood irritability and a history of parental depression (Propper et al., 2017; Krieger et al., 2013; Wiggins et al., 2018; Brotman et al., 2007), in coherence with our findings. Moreover, two twin-studies suggested that the association between irritability and depression might be, in part, genetically mediated (Stringaris et al., 2012; Savage et al., 2015). Another study showed that irritability partly mediated the link between maternal depression and depression in adolescents (Whelan et al., 2015). Future research would help better disentangling the interplay between risk factors for depression, irritability, and depressive disorders in adoles- cence and adulthood, and clarifying transition pathways from one disorder to the other.

Third, our study has several evaluation and therapeutics implica- tions. With respect to our findings, clinicians caring for youths with DMDD should better recognize clinical dimensions generally associated with internalized symptoms, in particular suicidal behaviors, the pre- sence of adverse life events, and the presence of trauma-related symp- toms. Second, some therapeutic interventions for DMDD have been justified by the association with depression (Benarous et al., 2017b). As depression and irritability might share common pathophysiological

mechanisms (Stringaris et al., 2012; Savage et al., 2015; Vidal- Ribas et al., 2018), effective treatment for the former could be useful for the later. So far, only one randomized controlled trial showed that a positive effect of 8 weeks of citalopram, a selective serotonin reuptake inhibitor (SSRI), in youths with SMD + ADHD previously treated by methylphenidate (Towbin et al., 2019).

In conclusion, we identified DMDD as a distinct entity from MDD and/or PDD in this clinical sample of outpatient youths. While we found some clinical features more specifically associated with DMDD (association with the externalized disorders and trauma-related dis- order, the severity of peer-relationship and school difficulties), the vulnerability factors studied were broadly comparable across disorders. Further studies are needed to confirm this findings and determine on which extend DMDD youths differ from those with other types of mood disturbances.

Funding

The study was funded by the Quebec Network on Suicide, Mood Disorders and Related Disorders RQSHA (grant: ASClin #2).

Disclosure

Dr. Benarous, Pr. Labelle, Pr. Guilé, Pr. Cohen, Dr. Renaud, and Dr. Breton report no biomedical financial interests or potential conflicts of interest.

Declaration of Competing Interest

None

Acknowledgments

The authors would like to thank Christophe Huynh Ph.D. for his help with data collection, Cosmin Lancu (psychiatry resident) for his assistance in studying the reliability of the chart review instrument's DMDD module, and Hughes Pellerin MSc for assistance with statistical analysis. Professor Guilé pursue his contribution during his time as invited researcher at the Center for Research and Intervention on Suicide, Ethical Issues and End-of-life practices (CRISE), Montreal, Canada. Therefore, the corresponding author would like to thank Pr Choukroun, Dean of Faculty of Medicine (Amiens) and Pr Mishara, Director of CRISE (Montreal).

Supplementary materials

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.jad.2020.01.020.

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