Neurocognitive function in pediatric bipolar disorder and disruptive mood dysregulation disorder and at risk for bipolar disorder

doi:10.21203/rs.3.rs-4921123/v1

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Neurocognitive function in pediatric bipolar disorder and disruptive mood dysregulation disorder and at risk for bipolar disorder

https://doi.org/10.21203/rs.3.rs-4921123/v1

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Objective: Neurocognitive function studies in Pediatric Bipolar Disorder (BPD) and Disruptive Mood Dysregulation Disorder (DMDD) are limited, despite substantial literature on their clinical presentation. This study aims to comparatively evaluate the neuropsychological characteristics of children and adolescents diagnosed with BPD, DMDD, and those at risk for bipolar disorder.

Method: We administered the neurocognitive battery to 120 participants aged 8-18 with BPD (n = 30), at-risk for bipolar disorder (n= 25), DMDD (n = 36) and healthy controls (n = 29). The neurocognitive battery included the Continuous Performance Test, Wisconsin Card Sorting Test, Stroop Color and Word Test, Trait Making Test A and B, California Verbal Learning Test-Child version.

Results: There were significant impairments in sustained attention, processing speed, cognitive flexibility, response prevention, verbal memory, and working memory in the BPD and DMDD groups, and in sustained attention in the at-risk group compared with controls. Impairments in verbal memory remained in the BPD and DMDD groups after controlling for current IQ score. After excluding ADHD diagnoses, deficits in sustained attention persisted in the at-risk group versus controls.

Conclusion: This study is the first to directly compare the neurocognitive profiles of children and adolescents with DMDD, BPD, and at risk for BD. The study highlights significant neurocognitive impairments within BPD and DMDD. The persistence of sustained attention deficits after excluding ADHD diagnoses suggests that sustained attention may be an endophenotype in the at-risk group.

Child and Adolescent

Neurocognitive Functions

Pediatric Bipolar Disorder

Disruptive Mood Dysregulation Disorder

Bipolar disorder (BD) is one of the childhood psychiatric disorders that most interferes with normal development and psychological functioning. While it used to be debated whether bipolar disorder existed in childhood, in recent years it has become widely accepted worldwide that bipolar disorder can be diagnosed in childhood, and the debate has focused more on clinical presentation.

Over the past two decades, the clinical diagnosis of pediatric bipolar disorder (BPD) has increased dramatically [1]. The increase in diagnoses of BPD is likely due in part to the fact that some researchers have conceptualized non-episodic severe irritability as a core feature of BPD [2, 3]. Others have argued that BPD, like adult bipolar disorder, is defined by the episodic nature of symptoms [4, 5]. Longitudinal studies have shown that children with chronic irritability are more likely to develop unipolar depression and anxiety disorders in adulthood, suggesting that children with 'chronic irritability' are not actually bipolar. To reduce the rate of BPD diagnoses and the resulting exposure to psychotropic medications [6], the Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-5) added Disruptive Mood Dysregulation Disorder (DMDD) to describe children with chronic irritability (American Psychiatric Association 2013). However, the diagnosis of DMDD has been controversial due to the lack of valid empirical studies and standard guidelines for pharmacological treatment, as well as the high rate of comorbidity [7, 8].

Many studies have shown that there are deficits in executive functions, verbal memory, verbal fluency and sustained attention in children and adolescents diagnosed with BPD[9, 10]. The fact that these deficits are present during both acute mood episodes and euthymic periods suggests that they may be 'endophenotypes' of bipolar disorder [11]. However, little is known about which cognitive deficits precede a bipolar disorder diagnosis and which develop as a result of illness onset and treatment. In DMDD, cognitive research is particularly limited. Compared to bipolar subjects, DMDD subjects showed decreased cognitive flexibility as assessed by a reversal learning task [12].

Family studies have shown that 7–22% of first-degree relatives of BD patients develop major mood disorders [13]. A number of recent studies have shown that the rate of cognitive deficits in unaffected at-risk relatives is much higher than in the general population [14, 15].It is thought that the cognitive deficits observed in unaffected at-risk relatives may be related to underlying 'neuropsychological traits' (endophenotype), as they cannot be explained by the disease or treatment [16].

Little is known about how to distinguish DMDD from other childhood psychiatric disorders and how to treat it, as it is a new diagnostic category defined in the DSM-5. Identifying the cognitive functions underlying psychopathology allows for a better understanding of pathogenesis and the development of effective treatments, in contrast to diagnostic manuals that focus on symptoms.

The aim of this study was to determine the similarities and differences in the neuropsychological characteristics of children and adolescents with BPD, DMDD and at-risk for BD, and to identify valid endophenotypes for bipolar disorder by examining the neuropsychological characteristics of cases at genetic high risk for BD. To our knowledge, this is the first study to directly compare the neuropsychological profiles of children and adolescents diagnosed with BPD, those at risk for BD, and those diagnosed with DMDD.

Population and Procedure

The original sample consisted of 120 participants aged 8–18 years. There are 4 groups in the study sample: BPD group, at-risk group, DMDD group, healthy control group. Thirty participants with a DSM-5 diagnosis of BPD, 36 participants with a DSM-5 diagnosis of DMDD, 25 participants at-risk for BD, and 29 healthy controls were included in the study from 2021 to 2022. The BPD and DMDD participants were recruited from outpatient and inpatient settings of child psychiatry clinic. The offsprings (n = 2) or siblings (n = 2) of cases diagnosed with BD in adult psychiatry were evaluated, and those who met the inclusion criteria were included in our study as the at-risk group. In addition, siblings (n = 21) of cases followed up with a diagnosis of BPD in the child psychiatry clinic who met the inclusion criteria were also included as the at-risk group. Children and adolescents without any chronic medical disease or known psychiatric disorder who applied to the adolescent health department were referred to the first author for the study. Following evaluation with the Kiddie Schedule for Affective Disorders and Schizophrenia for School-Age Children ─ Present and Lifetime Version (K-SADS-PL, DSM-5) by the first author, those who did not meet criteria for any psychiatric diagnosis and had no family history of major psychiatric disorders (such as schizophrenia, bipolar disorder, or major depressive disorder) were included in the healthy control group. Inclusion criteria for all groups were: age between 8 and 18 years; euthymia on enrollment [CDRS score ≤ 19, YMRS-ABF score ≤ 12], IQ score > 70. Exclusion criteria for all groups: concurrent active psychotic symptoms, autism spectrum disorder, visual and/or hearing impairment, unstable or major medical/neurological illness, lifetime DSM-5 substance use disorder.

This study was approved by Non-Interventional Clinical Research Ethics Committee with the date 14.07.2021 and decision number E2-21-660. All participants were assessed by the interviewer (first author) using K-SADS-PL. The sociodemographic form was completed based on information obtained from parents. While participants were administered the Children's Depression Rating Scale (CDRS) and the Youth Self-Report (YSR), their families were administered the Young Mania Rating Scale/Parent Form (YMRS-P), and the Child Behavior Checklist (CBCL). While depressive symptoms were assessed with the CDRS, manic symptoms were assessed with the YMRS-P. On the YMRS-P scale, the average score for a manic episode is 25, while the average score for a hypomanic episode is 20. Scores above 13 indicate possible mania or hypomania, and scores above 21 indicate mania or hypomania.

Following the clinical assessment, the participants were administered a neurocognitive test battery by the interviewer (first author) in a single session; this was completed in a total of two hours, with a 15-min rest period. For psychometric assessment, the Wechsler Intelligence Scale for Children-Revised (WISC-R) was administered by an expert psychologist to participants under 16 years of age, and the Wechsler Adult Intelligence Scale-Revised (WAIS-R) was administered to participants over 16 years of age.

Neurocognitive assessment

The neurocognitive tests used in our study were the E-Prime 3.0 (PST) software. The neurocognitive assessment was conducted by the clinician (first author). The tests in the neurocognitive battery used in our study were selected to represent measures and structures that have been found in the literature to be impaired in adults and adolescents with bipolar disorder.

Continuous Performance Test (CPT): The first version of the Continuous Performance Test (AX version) was designed to assess the deficit in the area of "sustained attention" in people with brain damage[17]. It is administered with letters that appear and disappear on a computer screen. The "AX-CPT" was used in our study and the total duration of the test is 15 minutes. In general, omission errors are associated with carelessness, and commission errors are associated with impulsivity.

Wisconsin Card Sorting Test (WCST): It was developed by Berg in 1948, and the manual of the test was prepared with modifications by Heaton and his colleagues in 1981 and 1993 [18]. This test is used to assess functions such as problem solving, reasoning, organization, sequencing, response inhibition, response mechanism shifting, abstract reasoning, and sustaining attention.

Stroop Color-Word Interference Test (SCWT): This test was first developed by Stroop in 1935 as an experimental task for the assessment of selective attention and response inhibition [19]. In the SCWT, processing speed was assessed with scores related to congruent stimuli, and interference (response inhibition) was assessed with scores related to incongruent stimuli.

Trail Making Test (TMT A\B): The Trail Making Test was developed by Reitan in 1958 [20]. Time to complete and number of errors are scored. Part A measures psychomotor speed and attention, and part B measures the ability to change set-shifting and visual scanning speed. A normative study was conducted on Turkish children aged 6 to 18 years [21].

California Verbal Learning Test-for Children (CVLT-C): This test was developed by Delis et al. (1987) for the assessment of verbal memory in adults [22], and the children's version was standardized in 1994 [23]. The CVLT-C assesses the learning process, permanence of learning over time, short- and long-term memory functions, learning strategies, storage-retrieval, and susceptibility to interfering stimuli. In our study, the form of this test translated by Prof. Dr. Hakan Gürvit at Istanbul University Faculty of Medicine, Department of Neurology was used.

Wechsler Intelligence Scale for Children-Revised (WISC-R) and Wechsler Adult Intelligence Scale-Revised (WAIS-R): The WISC-R is an intelligence test developed by Wechsler for children between the ages of 6 and 16. A validity and reliability study were conducted on Turkish children [24]. The WAIS-R was developed by David Weschler in 1955. It is used from 16 years of age. It is an individually administered intelligence test. Its Turkish translation was made in 1972 [25].

Statistical Analysis

Data analysis was performed using IBM SPSS 25.0 (SPSS Inc., Chicago, IL, USA). The Shapiro-Wilks test was used to assess the suitability of the data for normal distribution in groups, and the Levene test was used to assess homogeneity of variances. Comparisons between groups were evaluated using one-way analysis of variance when the assumption of normal distribution was met, and the Kruskal Wallis test when it was not. Based on these tests, multiple comparison tests were performed using the Tukey and Dunn Bonferroni tests, respectively. Categorical variables were evaluated using Pearson chi-square or Fisher's exact test, as appropriate. The relationship between quantitative variables was examined using the Spearman test. One-way multivariate analysis of covariance (MANCOVA) was performed to reduce the risk of type 1 error that can occur with multiple analyses. In this analysis, nine neurocognitive and two clinical measures were taken as dependent variables, group membership (BPD, DMDD, at-risk, control) as factor, and current Intelligence Score (IQ) as covariate. For each dependent variable that was significant in this multivariate model, an attempt was made to determine the differences between groups corrected for intelligence score using one-way analyses of covariance (ANCOVA) followed by the Bonferroni multiple comparison test. Results were considered statistically significant when p < 0.05.

Clinical Features

The demographic and clinical characteristics of the study groups were shown in Table 1. Most of the cases had comorbid diagnoses; 58% met the criteria for at least one other current disorder, most commonly an anxiety disorder and/or ADHD. There was no significant difference in full scale IQ scores between the BPD, DMDD, and at-risk groups (ps < .05), with the control group scoring higher than the others (p < .001) (Table 1). On the “total problems” subscale of the Child Behavior Checklist (CBCL), the BPD group scored significantly higher than the control group, and the DMDD group scored significantly higher than the at-risk and control groups (p < .001). On the "total problems" score of the Youth Self Report (YSR), the BPD and DMDD groups scored significantly higher than the control group (p = .003) (see Supplementary Table S1, available online).

Table 1

Demographic and clinical characteristics
	BPD⁰	Risk¹	DMDD²	Control³	Analysis	Group
	n = 30	n = 25	n = 36	n = 29	p	Difference (0,1,2,3)
Demographics Age (years), mean (SD) Gender, male (%) Education (years), median (range)	16.1 (1.4) 5 (16.7) 11 (8–12)	14.0 (3.1) 9 (36.0) 9 (2–12)	12.4 (2.3) 20 (55.6) 7 (2–11)	14.3 (2.4) 9 (31.0) 7 (3–12)	< 0.001^* 0.011^ < 0.001^*	0 > 1 > 3 > 2 2 > 0 2 < 0,1,3
Full Scale IQ, median (range)	80.5 (58–118)	98.0 (71–122)	96.0 (61–121)	110 (95–128)	< 0.001^***	3 > 0,1,2
Bipolar diagnosis, n (%) I II OS	21 (70) 7 (23) 2 (7)	-	-	-
Comorbid, n (%) ADHD GAD	9 (30.0) 10 (33,3)	10 (40.0) 7 (28,0)	30 (83.3) 12 (33,3)	- -	< 0.001^c 0.006^*	2 > 0,1 1 < 0,2
CDRS, median (range)	14.0 (3–19)	12.0 (2–19)	16.0 (3–28)	7.00 (1–19)	0.003^***	2 > 3
YMRS-P, median (range)	5.50 (0–12)	4.00 (0–11)	6.00 (0–11)	1.00 (0–12)	< 0.001^***	3 < 0,2
CBCL, median (range) Dysregulation profile Total problems	197 (151–243) 64.5 (37–82)	173 (151–225) 60.5 (38–75)	195 (160–241) 68.0 (51–79)	163 (150–214) 54.0 (29–75)	< 0.001^* 0.003^*	0 > 3,2 > 1,3 3 < 0,2
YSR, median (range) Total Problems	62.5 (42–88)	64.0 (42–73)	65.0 (28–77)	53.0 (37–76)	< 0.001^***	0 > 3, 2 > 1,3
Medication Antipsychotic, n (%) Antiepileptic, n (%) Lithium, n (%) Antidepressants, n (%) Combination therapy^a, n (%)	28 (93) 15 (50) 10 (33) 3 (10) 28 (97)	7 (28) - - 8 (32) 6 (24)	14 (39) - - 14 (39) 20 (57)	- - - - -

^*One Way Anova, ^**Pearson Chi-Square, ^***Kruskal Wallis Test

(0: BPD group, 1: Risk group, 2: DMDD group, 3: Control group) ^aCombination of two or more different psychotropic medications

ADHD, Attention Deficit and Hyperactivity Disorder; GAD, Generalized Anxiety Disorder; BD-OS, Bipolar Disorder-Other Specified; CDRS, Children's-Depression-Rating-Scale; YSR, Youth-Self-Report; YMRS-P, Young-Mania-Rating Scale/Parent Form; CBCL, Child-Behavior-Checklist.

Neurocognitive Performance

Table 2 shows the comparison of the neurocognitive tests between the groups. On the CPT test, omission and commission error scores (Om.Errors, Com.Errors) were significantly higher in the BPD, DMDD, and at-risk groups than in the control group. There were no statistically significant differences between groups on any subscale of the Wisconsin Card Sorting Test (WCST). On the Stroop, the groups differed significantly in commission errors for congruent stimuli (ST.Con.com), in commission errors for incongruent stimuli (ST.Incon.com), and target response to incongruent stimuli (ST.TR.Incon) subscores (Table 2). There were statistically significant differences between the groups in average time to complete part A (TMT.A), average time to complete part B (TMT.B), number of errors in part B (TMT.B-error), and total number of errors (TMT.AB-error) on the TMT A/B test (Table 2). On the CVLT-C, there were statistically significant differences between the groups in the scores for List A-Trial 1ࣧfree recall (A1), List A-totalࣧTrials 1–5 (A1_5), Short DelayedࣧFree-Recall (A_SDFR), Long DelayedࣧFree-Recall (A_LDFR), Short CuedࣧRecall (A_SCR), Long CuedࣧRecall (A_LCR), and Correct Recognition (CR) (Table 2). The BPD group scored significantly lower than the control group on the digit span subtest. On the digit symbol coding subtest, the BPD group had significantly lower scores than other groups, while the DMDD group had significantly lower scores than the control group. The BPD group scored significantly lower than the at-risk and control groups on the Working Memory Index (WMI) (Table 2).

Table 2

Neurocognitive performance
	BPD n = 30	Risk n = 25	DMDD n = 36	Control n = 29	Analysis
	Mean (SD)				F^(df=3)	p
CPT: Sustained Attention Om.Errors Com.Errors	26.77±31.29^a 15.20±21.34^a	24.52±24.54^a 11.52±26.56^a	24.00±15.98^a 9.72±23.19^a	9.31±13.28 3.03±11.43	3.809 1.672	0.012 0.177
SCWT: Working memory, Response Inhibition ST.Con.com ST.Incon.com ST.TR.Incon	1.97 ± 2.671^a 14.07 ± 18.983^a 72.17 ± 21.436^a	1.00 ± 1.258 6.92 ± 6.184 78.92 ± 16.109	2.47 ± 3.167^a 11.61 ± 11.716^a 76.08 ± 15.385	0.59 ± 1.181 4.21 ± 3.968 84.34 ± 9.155	4.274 4.107 2.985	0.007 0.008 0.034
TMT A/B TMT.A: Visual Attention TMT.B: Cognitive Flexibility TMT.Aerror TMT.Berror TMT.ABerror	101017 ± 27882 252842 ± 140827 1.0 ± 1.2 7.1 ± 7.7^a 8.1 ± 7.7^a	104169 ± 31919 244526 ± 137822 1.1 ± 1.0 7.3 ± 10.4 8.4 ± 10.8	117285 ± 42535 ^a 263372 ± 91334^a 1.2 ± 1.2 5.6 ± 7.0^a 6.8 ± 7.4^a	91939 ± 28795 173116 ± 69205 0.7 ± 0.6 1.8 ± 1.9 2.6 ± 1.9	3.134 4.030 1.263 3.485 3.695	0.028 0.009 0.290 0.018 0.014
CVLT-C: Verbal learning and memory A1 A1_5 A_SDFR A_LDFR A_SCR A_LCR CR	4.03 ± 1.671 29.80 ± 9.546^a 6.30 ± 2.793^a 6.17 ± 2.408^a 7.10 ± 2.454^a 7.20 ± 2.455^a 11.50 ± 2.129^a	3.88 ± 1.424 33.68 ± 9.716 8.20 ± 2.415 8.12 ± 2.438 8.48 ± 2.888 8.64 ± 2.660 12.16 ± 2.135	3.50 ± 1.276^a 30.47 ± 8.105^a 7.00 ± 2.461^a 6.64 ± 2.463^a 7.17 ± 2.249^a 7.14 ± 2.072^a 11.92 ± 1.795	4.79 ± 1.544 38.38 ± 9.994 9.62 ± 3.075 8.97 ± 2.732 9.38 ± 2.744 9.34 ± 2.807 12.93 ± 1.926	4.206 5.358 8.698 7.950 5.577 5.869 2.715	0.007 0.002 < 0.001 < 0.001 0.001 < 0.001 0.048
FSIQ	85.27 ± 15.737^a	97.32 ± 12.378^a	93.36 ± 14.965^a	111.41 ± 9.504	19.322	< 0.001
Digit Span: Working memory	6.67 ± 4.310^a	7.48 ± 3.393	7.08 ± 2.511	8.66 ± 4.287	1.631	0.186
Digit Symbol: Processing speed	7.17 ± 2.520^a,b,c	10.56 ± 3.001	10.17 ± 3.000^a	12.14 ± 2.774	15.875	< 0.001
WMI: Working memory	10.83 ± 6.481^a,b	15.64 ± 6.867	15.08 ± 5.432	17.83 ± 8.120	5.608	0.001

One Way Anova, ^a versus controls; ^b versus at-risk group; ^c versus DMDD group

(Om.Errors, Omission-Errors; Com.Errors, Commission-Errors; ST.Con.com, Stroop-Congruency-Commission-Errors; ST.Incon.com, Stroop-Incongruency-Commission-Errors; ST.TR.Incon, Stroop-Target-Respond-Incongruency; TMT.A, A-time, millisecond; TMT.B, B-time, millisecond; TMT.Aerror, A-error; TMT.Berror, B-error; TMT.ABerror, Total-error; A1, List A-Trial 1ࣧfree recall; A1_5, List A-totalࣧTrials 1–5; A_SDFR, Short-Delayed-Free-Recall; A_LDFR, Long-Delayed-Free-Recall; A_SCR, Short-Cued-Recall; A_LCR, Long-Cued-Recall; CR, Correct-Recognition; FSIQ, Full-Scale IQ; WMI, Working-Memory-Index)

Additional analyses

Nine neurocognitive measures that showed significant differences between groups were included in further analyses to maintain statistical power. The relationship between these nine neurocognitive measures and the total intelligence score was statistically significant. A significant overall difference in neurocognitive performance between groups was found after controlling for current IQ score [MANCOVA F(33, 321) = 1.506] Pillai's trace = 0.41; partial eta squares = 0.134]. As a result of the ANCOVA, the A_SDFR and A_LDFR subscores of the CVLT-C showed a statistically significant difference between the groups. In pairwise comparisons, the BPD group and the DMDD group scored significantly lower than the control group on the A_SDFR subscore. Mean neurocognitive performance between groups and corresponding univariate analyzes of covariance were shown in Table 3.

Table 3

Mean neurocognitive performance across groups and related univariate analyzes of covariance
	BPD n = 30	Risk n = 25		DMDD n = 36		Control n = 29			ANCOVA
	BPD n = 30	Risk n = 25		DMDD n = 36		Control n = 29			(df = 3, 115)
	Mean (SS)^a							F		p
CDRS	12.3 (7.1)		10.8 (5.8)		14.2 (5.9)^b		7.9 (10.9)		4.341	.006
YMRS-P	6.1 (4.4)^b		4.0 (3.6)		5.8 (3.7)^b		4.4 (6.8)		3.786	.012
Om.Errors	19.1 (26.8)		24.9 (21.7)		23.7 (22.2)		9.3 (40.8)		1.002	.395
Com.Errors	8.5 (25.4)		12.2 (20.6)		9.9 (21.0)		2.4 (38.7)		0.290	.833
ST.TR.Incon	78.0 (19.4)		79.1 (15.7)		76.8 (16.1)		81.0 (29.6)		0.478	.698
TMT.A	93898.2 (42148.3)		104366.3 (34154.1)		117894.7 (34855.6)		94180.5 (64140.3)		2.468	.066
TMT.B	228573.5 (137822.8)		245818.8 (111682.0)		258727.3 (113975.9)		196255.2 (209735.4)		1.377	.253
A1_5	33.5 (11.1)		33.6 (9.0)		30.9 (9.1)		35.4 (16.8)		1.066	.366
A_SDFR	6.8 (3.3)^b		8.2 (2.7)		7.1 (2.7)^b		8.2 (5.0)		3.713	.014
A_LDFR	7.0 (3.0)		8.1 (2.4)		6.7 (2.5)		7.6 (4.6)		2.712	.048
CR	12.1 (2.4)		12.2 (2.0)		11.9 (2.0)		12.5 (3.8)		0.802	.495
^a = Common variables (covariates) appearing in the model are evaluated at “FSIQ = 96.53” values. ^b versus controls (Bonferroni)

One-Way Analysis of Covariance (ANCOVA), Pairwise Comparison with Bonferroni on significant results.

(FSIQ = Full-Scale IQ; CDRS, Children's-Depression-Rating-Scale; YMRS-P, Young-Mania-Rating-Scale/Parent Form; Om.Errors, Omission-Errors; Com.Errors, Commission-Errors; ST.TR.Incon, Stroop-Target-Respond-Incongruency; TMT.A, A-time, millisecond; TMT.B, B-time, millisecond; A1, List A-Trial 1ࣧfree recall; A1_5, List A-totalࣧTrials 1–5; A_SDFR, Short-Delayed-Free-Recall; A_LDFR, Long-Delayed-Free-Recall; CR, Correct-Recognition)

The effect of Attention Deficit and Hyperactivity Disorder on neurocognitive processes

In our study, the comorbid diagnosis of Attention Deficit and Hyperactivity Disorder (ADHD) was 30% (n = 9) in the BPD group, 40% (n = 10) in the at-risk group, and 83.3% (n = 30) in the DMDD group. To determine the possible confounding effect of ADHD comorbidity, neurocognitive tests that showed significant differences between groups were re-evaluated after excluding ADHD comorbidity; the BPD, DMDD, and at-risk groups scored significantly higher than the control group on the AX-CPT in terms of "omission errors" and "comission errors" and the TMT.B subscore. The BPD group scored significantly lower than the control group on ST.TR.InCon, A1_5, CR, and Working Memory Index. On A_SDFR and A_LDFR scores, the BPD group scored significantly lower than the at-risk and control groups, and the DMDD group scored significantly lower than the control group. On the WISC-R/WAIS-R digit span subtest, the BPD group scored significantly lower than the at-risk, DMDD, and control groups.

There are very few studies evaluating neurocognitive function in BPD and DMDD, although there is a substantial literature on the clinical presentation of these disorders. To our knowledge, this is the first study to directly compare the neurocognitive profiles of children and adolescents diagnosed with BPD, those at-risk for BD, and those diagnosed with DMDD. Our main findings revealed distinct neurocognitive profiles among the three groups; the BPD group showed the most severe neurocognitive impairment, followed by the DMDD group and the at-risk group. The BPD group exhibited significant impairment in all tests except WCST. The cases with a total IQ score of over 70 were included in our study. Many studies have included subjects with IQ scores above 70 or 80[26–28] because IQ scores may influence neurocognitive outcomes.

Our study suggests that the BPD, DMDD, and at-risk groups have significant deficits in sustained attention compared to controls. Neurocognitive research on potential sustained attention deficits in youth with BPD is equivocal. While some studies have found no significant difference between BPD and controls on the Continuous Performance Test (CPT) [29, 30]; others have reported significantly poorer performance in the BPD group compared to controls on the CPT [31, 32], consistent with our findings. For youth at-risk for BD, Brotman et al (2009) found increased response time on the CPT in youth with first-degree relatives with BD, regardless of psychopathology [33]. This study found that the at-risk group showed impairment only in sustained attention compared to the control group. Studies with larger samples are needed to confirm these data.

In studies evaluating working memory on various tasks between BPD and at-risk subjects, deficits were more consistently found in the BPD group than in the at-risk group[34, 35]. Consistent with previous research, our study found working memory impairments in the BPD group compared to control group.

This study found significant deficits in response inhibition, cognitive flexibility, verbal memory, and processing speed in the BPD and DMDD groups compared to control group. Response inhibition, assessed by the Stroop Color-Word Interference Task (SCWT) and its variants, has been reported impaired in BPD in most studies[36, 37]. Moreover, most studies assessing cognitive flexibility with the Trail Making Test-Part B (TMT-B) have found significant deficits in BPD patients [37, 38]. Research on cognitive flexibility in the at-risk group is equivocal, with some studies reporting deficits[39, 40] and others finding no deficits [39, 41]. Most studies assessing processing speed in BPD [36] and at-risk cases [39] using the Wechsler Adult Intelligence Scale (WAIS) digit symbol coding subtest found significant deficits in BPD and at-risk cases. Additionally, our findings suggest that children with DMDD may exhibit impairments in cognitive flexibility. This finding is in line with research indicating diminished cognitive flexibility in children diagnosed with DMDD[42, 43].

According to a meta-analysis, there is consistent evidence of impaired verbal memory functions as measured by the CVLT-C. In line with existing research, this study identified significant impairments in verbal memory in both the BPD and DMDD groups compared to the control group. Given that no other studies have assessed verbal memory in DMDD, this study provides the first data on this topic. However, no significant difference in verbal memory was found between the at-risk and control groups. The results of the CVLT-C in the at-risk group are also inconsistent across studies; while some have reported deficits, others have found no differences. After controlling for current IQ scores, only impairment in the verbal memory domain remained significant among the neurocognitive domains affected in the BPD and DMDD groups compared to the control group. Therefore, our study suggests that verbal memory functions are the most consistently and severely impaired in both the BPD and DMDD groups.

Many authors have reported BD and ADHD to be highly comorbid in childhood [44, 45]. In general, while studies have examined neuropsychological functioning in childhood ADHD and adult BD, there are very few neuropsychological studies of children and adolescents with BD [30]. After excluding ADHD diagnoses, impairments in processing speed, sustained attention, cognitive flexibility, response inhibition, verbal memory, and working memory remained evident in the BPD group. This persistence may reflect the neurocognitive effects of BPD on these domains, independent of ADHD. In the at-risk group, deficits in sustained attention remained after excluding ADHD diagnoses, suggesting that sustained attention could be an endophenotype. Similarly, impairments in sustained attention and verbal memory remained in the DMDD group after excluding ADHD comorbidity. However, due to the high rate of ADHD comorbidity and the resultant small sample size in the DMDD group, larger studies are needed to validate these findings.

There are several limitations to our study. The first is that the BPD group included all BD subtypes (BD 1, BD 2, and BP OS). Due to our relatively small sample size, neurocognitive differences between subtypes could not be fully evaluated. Second, the at-risk group represents a heterogeneous group consisting of children and siblings. Third, because this was a naturalistic study, the effect of medication use on neurocognitive factors could not be examined in our study. Fourth, it contains a heterogeneous sample, as age and gender matching cannot be made between the groups due to the fact that it includes less frequently encountered cases in the clinic. Fifth, the cross-sectional design of our study limits the possibility of searching for causal relationships. Comparison of subgroups by repeated statistical analysis carries the risk of spurious findings, even if the main findings survive correction for multiple testing.

This study is the first to directly compare the neurocognitive profiles of children and adolescents with DMDD, BPD and at-risk for BD using a comprehensive neurocognitive test battery that includes more specific consensus-based measures for bipolar disorder. Previous studies have mostly assessed social processing in DMDD; no studies have been found that comprehensively assess other neurocognitive functions in DMDD. This study provides a framework for understanding the cognitive deficits found in BPD and DMDD that have direct clinical implications. The recognition of these neurocognitive deficits in children with BPD and DMDD, and the development of individualized educational plans and school-based interventions for these cases, should be considered a goal of treatment. Given the limitations of our study, these data should be considered preliminary. Future prospective follow-up and imaging studies with larger samples and a broader neurocognitive test battery might better characterize the neuropsychological features of the BPD, at-risk, and DMDD groups.

Author Contribution

İsranur Yenen Sivri: Conceptualization, data curation, investigation, methodology, resources, writing, original draft preparation, reviewing and editing. Ayşe Selma Y. Menderes: Data curation, investigation, resources and reviewing. Seda Beğli: Data curation. Kazım Cihan Can: Data curation. Demet Taş: Data curation. Esra Çöp: Conceptualization, project administration, supervision, review and editing.

Acknowledgement

The authors thank to the adolescents and their parents who participated in the study.

Data Availability

The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.

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No competing interests reported.

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Neurocognitive function in pediatric bipolar disorder and disruptive mood dysregulation disorder and at risk for bipolar disorder

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Abstract

Introduction

METHOD

Population and Procedure

Neurocognitive assessment

Statistical Analysis

RESULTS

Clinical Features

Neurocognitive Performance

Additional analyses

The effect of Attention Deficit and Hyperactivity Disorder on neurocognitive processes

DISCUSSION

Conclusions

Declarations

Author Contribution

Acknowledgement

Data Availability

References

Additional Declarations

Supplementary Files

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Version 1