- Email: [email protected]
Are autistic traits in youth meaningful? A replication study in non-referred siblings of youth with and without ADHD
P.7.b. Child and adolescent disorders and treatment − Disorders (clinical) and structure of brain regions involved in emotion identification and reactivity, including the amygdala, hippocampus, striatum, and orbitofrontal cortex, as well as areas involved in emotional regulation, such as dorsolateral prefrontal cortex and anterior cingulate cortex [1]. It is unclear, however, whether these differences reflect the clinical state of major depression or neurobiological traits that predispose individuals to be at risk for major depression. Objective: The main aim of the present study was to identify structural, task based, and resting state fMRI based neural underpinnings of the risk for major depression. Method: We collected fMRI scans of 38 unaffected children of parents with (at-risk children) and 23 age-matched children without (controls) histories of major depression. We examined structural differences within the two groups. We compared the task based activation patterns of the two groups while the children were engaged in a simple perceptual-matching task of happy, fearful, and neutral faces. We also compared resting-state functional connectivity between at-risk children and controls, focusing on regions of interest in the default mode network (DMN), cognitive control network, and affective network. Result: The resting-state scans showed hyperconnectivity between the DMN and subgenual anterior cingulate cortex (ACC) in at-risk children compared to controls, and the magnitude of connectivity positively correlated with symptom scores. Compared to controls, at-risk children also had hypoconnectivity within the cognitive control network, lower connectivity between the left dorsolateral prefrontal cortex (DLPFC) and subgenual ACC, and hyperconnectivity between the right amygdala and right inferior frontal gyrus. Classification between at-risk children and controls based on these resting-state connectivity differences yielded high accuracy with high sensitivity and specificity that exceeded clinical ratings. Among the group who completed the face-matching task, the at-risk group showed increased activation to fearful relative to neutral facial expressions in the amygdala and multiple cortical regions, and decreased activation to happy relative to neutral facial expressions in the anterior cingulate cortex and supramarginal gyrus compared to controls. At-risk children also exhibited reduced amygdala volume. Conclusion: Unaffected children at-risk for major depression exhibited atypical functional connectivity in the default mode, cognitive control, and affective networks, as well as different patterns of activation in the amygdala and surrounding regions and a decreased amygdala volume. These results identify neural biomarkers of risk for major depression in children that could improve the identification of children at very high risk for major depression and who could then be targeted for early intervention to reduce the likelihood of developing major depression. Longitudinal follow-up studies of at-risk children could help determine whether such neurobiological biomarkers could improve the identification of children who will actually develop major depression or other major psychiatric disorders. References [1] Stuhrmann, A., Suslow, T., Dannlowski, U., 2011. Facial emotion processing in major depression: a systematic review of neuroimaging findings. Biol Mood Anxiety Disord 1:10. Disclosure statement: Dr. Joseph Biederman is currently receiving research support from the following sources: The Department of Defense, Food & Drug Administration, Lundbeck, Merck, Neurocentria Inc., PamLab, Pfizer, Shire Pharmaceuticals Inc., SPRITES, Sunovion, and NIH. In 2016, Dr. Biederman received honoraria from the MGH Psychiatry Academy for tuitionfunded CME courses, and from Avekshan, Alcobra and AACAP. He has a US Patent Application pending (Provisional Number #61/233,686) through
S715
MGH corporate licensing, on a method to prevent stimulant abuse. In 2015, Dr. Biederman received honoraria from the MGH Psychiatry Academy for tuition-funded CME courses, and from Avekshan. He received research support from Ironshore, Magceutics Inc., and Vaya Pharma/Enzymotec. This work was supported by The Tommy Fuss Fund and the Pediatric Psychopharmacology Council Fund.
P.7.b.004 Are autistic traits in youth meaningful? A replication study in non-referred siblings of youth with and without ADHD J. Biederman1 ° , R. Fried1 , G. Joshi1 Hospital, Psychiatry, Boston, USA
1 Massachusetts
General
Background: Recent studies showed that symptoms of autistic traits (ATs) appear in 20 to 30 percent of children with ADHD [1−3]. Children with ADHD and ATs appear to be more impaired and dysfunctional than children with ADHD and no ATs. Consistent with these findings in the literature, we assessed the prevalence and correlates of ATs in youth with and without ADHD, where a diagnosis of autism was exclusionary [4]. ATs were operationalized using a profile from the Child Behavior Checklist (CBCL) using extreme values from the sum of the Withdrawn, Social, and Thought Problems T-scores [5]. We previously reported on the high prevalence and burden of significant autistic traits (ATs) in youth with ADHD that is associated with significantly greater impairment in psychopathological, interpersonal, educational, and neuropsychological functioning. Because the sample consisted of referred ADHD youth, uncertainties remain as to whether these findings generalize to non-referred populations of youths with and without ADHD. Objective: The main aim of the current study was to examine both the prevalence and correlates of ATs in non-referred youth with and without ADHD. To this end, we used data from an existing, large-scale sample of non-referred siblings of probands with and without ADHD. Based on the findings in probands, we hypothesized that ATs would be identifiable in non-referred siblings and that the presence of ATs would be associated with higher levels of morbidity and dysfunction. Method: Participants were non-referred siblings of ADHD (N = 257) and Control (N = 234) probands of longitudinal, casecontrol family studies conducted at the Massachusetts General Hospital. Assessments included measures of psychiatric, psychosocial, educational, and cognitive functioning. Presence of significant ATs were operationalized using the Child Behavior Checklist (CBCL) AT profile consisting of an aggregate score 195 for the sum of the Withdrawn, Social, and Thought Problems T-scores. Results: ATs were significantly more prevalent in siblings of ADHD probands compared to siblings of Control probands (6% vs. 1%, p = 0.02). Siblings of ADHD probands with a positive AT profile (N = 15) were significantly more impaired than those without an AT profile (N = 242) in psychopathological, interpersonal, educational, and neuropsychological functioning. Conclusions: Consistent with previous findings on ATs in a referred sample of youth with ADHD, the current study reports a higher than expected prevalence of ATs in a non-referred sample of siblings of youth with ADHD. The present study shows that ATs can be identified in a sizeable minority of non-referred children, and that such children are at high risk for significant morbidity and disability. The current findings suggest that elevated scores on the CBCL-AT subscale may indicate a need to clinically
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P.7.b. Child and adolescent disorders and treatment − Disorders (clinical)
assess for ASD, ADHD, mood, anxiety, and disruptive behavior disorders, emotional dysregulation, and impaired social and school functioning. These results provide further support for the clinical relevance of ATs irrespective of referral status. References [1] Grzadzinski, R., Di Martino, A., Brady, E., Mairena, M.A., O’Neale, M., Petkova, E, et al., 2011. Examining autistic traits in children with ADHD: does the autism spectrum extend to ADHD? J Autism Dev Disord 41(9):1178−91. [2] Kochhar, P., Batty, M.J., Liddle, E.B., Groom, M.J., Scerif, G., Liddle, P.F., et al., 2011. Autistic spectrum disorder traits in children with attention deficit hyperactivity disorder. Child Care Health Dev 37(1):103−10. [3] Mulligan, A., Anney, R.J., O’Regan, M., Chen, W., Butler, L., Fitzgerald, M., et al., 2009. Autism symptoms in Attention-Deficit/ Hyperactivity Disorder: a familial trait which correlates with conduct, oppositional defiant, language and motor disorders. J Autism Dev Disord 39(2):197–209. Epub 2008/07/22. [4] Kotte, A., Joshi, G., Fried, R., Uchida, M., Spencer, A., Woodworth, K.Y., et al., 2013. Autistic traits in children with and without ADHD. Pediatrics 132(3):e612−22. [5] Biederman, J., Petty, C.R., Fried, R., Wozniak, J., Micco, J.A., Henin, A., et al., 2010 Child behavior checklist clinical scales discriminate referred youth with autism spectrum disorder: a preliminary study. J Dev Behav Pediatr 31(6):485−90. Disclosure statement: Dr. Joseph Biederman is currently receiving research support from the following sources: The Department of Defense, Food & Drug Administration, Lundbeck, Merck, Neurocentria Inc., PamLab, Pfizer, Shire Pharmaceuticals Inc., SPRITES, Sunovion, and NIH. In 2016, Dr. Biederman received honoraria from the MGH Psychiatry Academy for tuitionfunded CME courses, and from Avekshan, Alcobra and AACAP. He has a US Patent Application pending (Provisional Number #61/233,686) through MGH corporate licensing, on a method to prevent stimulant abuse. In 2015, Dr. Biederman received honoraria from the MGH Psychiatry Academy for tuition-funded CME courses, and from Avekshan. He received research support from Ironshore, Magceutics Inc., and Vaya Pharma/Enzymotec. This work was supported by NIH grants R01MH050657 and R01HD036317 (JB), and by the Pediatric Psychopharmacology Research Council Fund.
P.7.b.005 Gender specific differences in auditory brain stem response in young patients with ADHD E. Claesdotter-Hybbinette1 ° , M. Cervin1 , S. Akerlund1 , M. R˚astam1 , M. Lindvall1 1 Dept of Clinical Sciences, Lund University, Lund, Sweden Objective: The auditory brainstem response (ABR) is often affected in neurodevelopmental disorders [1−3]. The aim of this study was to investigate possible gender differences in ABR between young females and young males with ADHD, compared to control subjects.
Method: We studied 63 females with ADHD (mean 13.8 years, SD 2.5), 26 female controls (mean 13.8 years, SD 2.7), 48 males with ADHD (mean 13.1 years, SD 1.8), and 20 male controls (mean 12.8 years, SD 1.7). All patients were diagnosed according to the DSM-IV. The ABR consists of seven positive peaks (wave I–VII) that occur 10 ms following a stimulus recorded by five electrodes; one reference electrodes on the mastoid processes of each ear and two active electrodes and one ground electrode placed on the forehead. Results: Comparing the ABR of 63 girls with ADHD to 26 age correlated control subjects 3 traits were identified, denoted TR6, TR14 and TR15. The higher value in TR6 (p = 0.000064), is explained by more aberrant curve profiles in the thalamic region. In TR14, the aberration was found in a region from superior olivary complex to thalamus (p = 0.00059). TR15 (p = 0.00035), is explained by more aberrant curve profiles in the lateral leminiscus. When looking at the ABR from 48 young males with ADHD and comparing them to 20 age correlated control subjects, we found 3 traits; TR4, TR5 and TR14. TR 4 is a lower correlation to a norm curve in inferior colliculus and thalamic area (p = 0.00105). TR5 identifies irregular curve profiles representing the nucleus cochlea (p = 0.00027). TR14, is described as an aberration in superior olivary complex to thalamus (p = 0.00013). Conclusion: These data indicate both gender specific aberrations in the ABR in ADHD subjects as well as specific response differences between ADHD subjects and normal controls. Young females with ADHD exhibited a significantly different ABR in a region between cochlear nucleus and superior olivary complex and in the thalamic region. Neither of these differences could be seen in the male ADHD group when compared to the male control subjects. However, in the male ADHD group ABR aberrancy was found in the midbrain region and in the more peripheral part; nucleus cocleus. Only one trait was different for both male and females between the ADHD group and the control subjects. The present study suggests that the ABR method might provide useful biomarkers to support the clinical diagnoses of ADHD. Further studies of ABR and other child and adolescent disorders such as Autism and OCD are in progress. References [1] Wong, V., Wong, S.N., 1991. Brainstem auditory evoked potential study in children with autistic disorder. J. Autism Dev. Disord. 21 (3), 329−40. [2] Schochat, E., Scheuer, CI., Andrade, E.R. 2002 ABR and auditory P300 findings in children with ADHD. Arq. Neuropsiquiatr. (60) 742–747. [3] Claesdotter-Hybbinette, E., Safdarzadeh-Haghighi, M., Rastam, M., Lindvall, M., 2015 Abnormal brainstem auditory response in young females with ADHD. Psychiatry Res. 08 229(3).
Table 1 (abstract P.7.b.005). ABR results for young patients with ADHD compared to controls. Trait
TR4 TR5 TR6 TR14 TR15
Females mean (S.D.); median ADHD (N = 63)
Controls (N = 26)
0.62 (0.29); 0.71 0.85 (0.14); 0.90 172 (56); 174 3.8 (1.8); 4 66 (47); 61
0.73 (0.19); 0.81 0.85 (0.22); 0.94 116 (49); 123 2.2 (1.9); 2 31 (24); 27
Mann–Whitney U test was used.
p-value
0.084 0.321 0.000064 0.00059 0.00035
Males mean (S.D.); median ADHD (N = 48)
Controls (N = 20)
0.57(0.26); 0.62 0.80 (0.18); 0.87 157 (63); 156 4.5 (1.8); 5 57 (42); 52
0.77 (0.18); 0.80 0.93 (0.06); 0.95 139 (64); 122 2.3 (1.8); 2 47 (34); 39
p-value
0.00105 0.00027 0.208 0.00013 0.518
S715
MGH corporate licensing, on a method to prevent stimulant abuse. In 2015, Dr. Biederman received honoraria from the MGH Psychiatry Academy for tuition-funded CME courses, and from Avekshan. He received research support from Ironshore, Magceutics Inc., and Vaya Pharma/Enzymotec. This work was supported by The Tommy Fuss Fund and the Pediatric Psychopharmacology Council Fund.
P.7.b.004 Are autistic traits in youth meaningful? A replication study in non-referred siblings of youth with and without ADHD J. Biederman1 ° , R. Fried1 , G. Joshi1 Hospital, Psychiatry, Boston, USA
1 Massachusetts
General
Background: Recent studies showed that symptoms of autistic traits (ATs) appear in 20 to 30 percent of children with ADHD [1−3]. Children with ADHD and ATs appear to be more impaired and dysfunctional than children with ADHD and no ATs. Consistent with these findings in the literature, we assessed the prevalence and correlates of ATs in youth with and without ADHD, where a diagnosis of autism was exclusionary [4]. ATs were operationalized using a profile from the Child Behavior Checklist (CBCL) using extreme values from the sum of the Withdrawn, Social, and Thought Problems T-scores [5]. We previously reported on the high prevalence and burden of significant autistic traits (ATs) in youth with ADHD that is associated with significantly greater impairment in psychopathological, interpersonal, educational, and neuropsychological functioning. Because the sample consisted of referred ADHD youth, uncertainties remain as to whether these findings generalize to non-referred populations of youths with and without ADHD. Objective: The main aim of the current study was to examine both the prevalence and correlates of ATs in non-referred youth with and without ADHD. To this end, we used data from an existing, large-scale sample of non-referred siblings of probands with and without ADHD. Based on the findings in probands, we hypothesized that ATs would be identifiable in non-referred siblings and that the presence of ATs would be associated with higher levels of morbidity and dysfunction. Method: Participants were non-referred siblings of ADHD (N = 257) and Control (N = 234) probands of longitudinal, casecontrol family studies conducted at the Massachusetts General Hospital. Assessments included measures of psychiatric, psychosocial, educational, and cognitive functioning. Presence of significant ATs were operationalized using the Child Behavior Checklist (CBCL) AT profile consisting of an aggregate score 195 for the sum of the Withdrawn, Social, and Thought Problems T-scores. Results: ATs were significantly more prevalent in siblings of ADHD probands compared to siblings of Control probands (6% vs. 1%, p = 0.02). Siblings of ADHD probands with a positive AT profile (N = 15) were significantly more impaired than those without an AT profile (N = 242) in psychopathological, interpersonal, educational, and neuropsychological functioning. Conclusions: Consistent with previous findings on ATs in a referred sample of youth with ADHD, the current study reports a higher than expected prevalence of ATs in a non-referred sample of siblings of youth with ADHD. The present study shows that ATs can be identified in a sizeable minority of non-referred children, and that such children are at high risk for significant morbidity and disability. The current findings suggest that elevated scores on the CBCL-AT subscale may indicate a need to clinically
S716
P.7.b. Child and adolescent disorders and treatment − Disorders (clinical)
assess for ASD, ADHD, mood, anxiety, and disruptive behavior disorders, emotional dysregulation, and impaired social and school functioning. These results provide further support for the clinical relevance of ATs irrespective of referral status. References [1] Grzadzinski, R., Di Martino, A., Brady, E., Mairena, M.A., O’Neale, M., Petkova, E, et al., 2011. Examining autistic traits in children with ADHD: does the autism spectrum extend to ADHD? J Autism Dev Disord 41(9):1178−91. [2] Kochhar, P., Batty, M.J., Liddle, E.B., Groom, M.J., Scerif, G., Liddle, P.F., et al., 2011. Autistic spectrum disorder traits in children with attention deficit hyperactivity disorder. Child Care Health Dev 37(1):103−10. [3] Mulligan, A., Anney, R.J., O’Regan, M., Chen, W., Butler, L., Fitzgerald, M., et al., 2009. Autism symptoms in Attention-Deficit/ Hyperactivity Disorder: a familial trait which correlates with conduct, oppositional defiant, language and motor disorders. J Autism Dev Disord 39(2):197–209. Epub 2008/07/22. [4] Kotte, A., Joshi, G., Fried, R., Uchida, M., Spencer, A., Woodworth, K.Y., et al., 2013. Autistic traits in children with and without ADHD. Pediatrics 132(3):e612−22. [5] Biederman, J., Petty, C.R., Fried, R., Wozniak, J., Micco, J.A., Henin, A., et al., 2010 Child behavior checklist clinical scales discriminate referred youth with autism spectrum disorder: a preliminary study. J Dev Behav Pediatr 31(6):485−90. Disclosure statement: Dr. Joseph Biederman is currently receiving research support from the following sources: The Department of Defense, Food & Drug Administration, Lundbeck, Merck, Neurocentria Inc., PamLab, Pfizer, Shire Pharmaceuticals Inc., SPRITES, Sunovion, and NIH. In 2016, Dr. Biederman received honoraria from the MGH Psychiatry Academy for tuitionfunded CME courses, and from Avekshan, Alcobra and AACAP. He has a US Patent Application pending (Provisional Number #61/233,686) through MGH corporate licensing, on a method to prevent stimulant abuse. In 2015, Dr. Biederman received honoraria from the MGH Psychiatry Academy for tuition-funded CME courses, and from Avekshan. He received research support from Ironshore, Magceutics Inc., and Vaya Pharma/Enzymotec. This work was supported by NIH grants R01MH050657 and R01HD036317 (JB), and by the Pediatric Psychopharmacology Research Council Fund.
P.7.b.005 Gender specific differences in auditory brain stem response in young patients with ADHD E. Claesdotter-Hybbinette1 ° , M. Cervin1 , S. Akerlund1 , M. R˚astam1 , M. Lindvall1 1 Dept of Clinical Sciences, Lund University, Lund, Sweden Objective: The auditory brainstem response (ABR) is often affected in neurodevelopmental disorders [1−3]. The aim of this study was to investigate possible gender differences in ABR between young females and young males with ADHD, compared to control subjects.
Method: We studied 63 females with ADHD (mean 13.8 years, SD 2.5), 26 female controls (mean 13.8 years, SD 2.7), 48 males with ADHD (mean 13.1 years, SD 1.8), and 20 male controls (mean 12.8 years, SD 1.7). All patients were diagnosed according to the DSM-IV. The ABR consists of seven positive peaks (wave I–VII) that occur 10 ms following a stimulus recorded by five electrodes; one reference electrodes on the mastoid processes of each ear and two active electrodes and one ground electrode placed on the forehead. Results: Comparing the ABR of 63 girls with ADHD to 26 age correlated control subjects 3 traits were identified, denoted TR6, TR14 and TR15. The higher value in TR6 (p = 0.000064), is explained by more aberrant curve profiles in the thalamic region. In TR14, the aberration was found in a region from superior olivary complex to thalamus (p = 0.00059). TR15 (p = 0.00035), is explained by more aberrant curve profiles in the lateral leminiscus. When looking at the ABR from 48 young males with ADHD and comparing them to 20 age correlated control subjects, we found 3 traits; TR4, TR5 and TR14. TR 4 is a lower correlation to a norm curve in inferior colliculus and thalamic area (p = 0.00105). TR5 identifies irregular curve profiles representing the nucleus cochlea (p = 0.00027). TR14, is described as an aberration in superior olivary complex to thalamus (p = 0.00013). Conclusion: These data indicate both gender specific aberrations in the ABR in ADHD subjects as well as specific response differences between ADHD subjects and normal controls. Young females with ADHD exhibited a significantly different ABR in a region between cochlear nucleus and superior olivary complex and in the thalamic region. Neither of these differences could be seen in the male ADHD group when compared to the male control subjects. However, in the male ADHD group ABR aberrancy was found in the midbrain region and in the more peripheral part; nucleus cocleus. Only one trait was different for both male and females between the ADHD group and the control subjects. The present study suggests that the ABR method might provide useful biomarkers to support the clinical diagnoses of ADHD. Further studies of ABR and other child and adolescent disorders such as Autism and OCD are in progress. References [1] Wong, V., Wong, S.N., 1991. Brainstem auditory evoked potential study in children with autistic disorder. J. Autism Dev. Disord. 21 (3), 329−40. [2] Schochat, E., Scheuer, CI., Andrade, E.R. 2002 ABR and auditory P300 findings in children with ADHD. Arq. Neuropsiquiatr. (60) 742–747. [3] Claesdotter-Hybbinette, E., Safdarzadeh-Haghighi, M., Rastam, M., Lindvall, M., 2015 Abnormal brainstem auditory response in young females with ADHD. Psychiatry Res. 08 229(3).
Table 1 (abstract P.7.b.005). ABR results for young patients with ADHD compared to controls. Trait
TR4 TR5 TR6 TR14 TR15
Females mean (S.D.); median ADHD (N = 63)
Controls (N = 26)
0.62 (0.29); 0.71 0.85 (0.14); 0.90 172 (56); 174 3.8 (1.8); 4 66 (47); 61
0.73 (0.19); 0.81 0.85 (0.22); 0.94 116 (49); 123 2.2 (1.9); 2 31 (24); 27
Mann–Whitney U test was used.
p-value
0.084 0.321 0.000064 0.00059 0.00035
Males mean (S.D.); median ADHD (N = 48)
Controls (N = 20)
0.57(0.26); 0.62 0.80 (0.18); 0.87 157 (63); 156 4.5 (1.8); 5 57 (42); 52
0.77 (0.18); 0.80 0.93 (0.06); 0.95 139 (64); 122 2.3 (1.8); 2 47 (34); 39
p-value
0.00105 0.00027 0.208 0.00013 0.518