Poster No:
360
Submission Type:
Abstract Submission
Authors:
JIANGYUN HOU1, Guido Wingen2, Dirk Smit2, Laurens Mortel2, Shu Liu2, Weijian Liu2
Institutions:
1Amsterdam UMC location University of Amsterdam, Amsterdam, North Holland, 2Amsterdam UMC location University of Amsterdam, Amsterdam, Noord-Holland
First Author:
JIANGYUN HOU
Amsterdam UMC location University of Amsterdam
Amsterdam, North Holland
Co-Author(s):
Guido Wingen
Amsterdam UMC location University of Amsterdam
Amsterdam, Noord-Holland
Dirk Smit
Amsterdam UMC location University of Amsterdam
Amsterdam, Noord-Holland
Laurens Mortel
Amsterdam UMC location University of Amsterdam
Amsterdam, Noord-Holland
Shu Liu
Amsterdam UMC location University of Amsterdam
Amsterdam, Noord-Holland
Weijian Liu
Amsterdam UMC location University of Amsterdam
Amsterdam, Noord-Holland
Introduction:
Many mental health issues are neurodevelopmental in nature with childhood and adolescence being a particularly sensitive period for onset of symptoms, which affect a significant number of adolescents1. Given the rising prevalence of mental health issues among adolescents in recent years, understanding the development of these conditions has become a critical public health objective. Here, we applied two separate linear models to examine between-group differences at baseline and the changes at 2 year follow up compared to baseline to identify the development of brain during the onset of mental health problems.
Methods:
We selected ABCD study2 participants with initial t-scores under 65 on the DSM-oriented CBCL scales, but who exceeded this threshold at two-year follow-up3. After excluding those without usable MRI data or a psychiatric history at baseline, our identified 55 individuals with ADHD, 94 with anxiety, 44 with conduct disorders, 105 with depression, 49 with oppositional defiant disorders, 144 with somatic symptoms, and 1679 controls. Our imaging data included 1876 image features from 6 modalities extracted: structural MRI, diffusion MRI, and functional MRI data (resting state MRI, task fMRI: Monetary Incentive Delay task (MID), task fMRI: stop signal task (SST), task fMRI: emotional n-back (EN-back))4. Then, we built two linear models including all controls: For baseline data: baseline data~ Group + Age +Sex +IQ + EA; For the changes from baseline to 2 year follow up: 2 year follow up data ~ Group+ baseline data + Age +Sex +IQ +EA in R for six disorders in six modalities to find if there any significant differences (p(FDR)<0.05/6) between healthy controls and patients with age, sex, IQ and educational level of parents (EA) as covariates. In addition, we also estimated correlation matrices of these six modalities based on the t values from above models to investigate the comparability of imaging effects across the disorders.
Results:
We found significant development of brain from three disorders:1. the ADHD group showed higher correlation between ventral attention network (VAN) and right caudate, and a lower correlation between VAN and right putamen than HC from resting state fMRI in the changes model. 2. Individuals with conduct problems showed decreased mean beta weights for task fMRI: SST correct stop versus incorrect stop contrast in left pallidum compared to HC in the changes model. 3. Oppositional defiant group showed increased volume in left cerebral white matter from structure MRI, and increased fiber tract volume of all DTI atlas tract fiber tracts, of DTI atlas tract in the left superior longitudinal fasiculus, in the left hemisphere and left hemisphere without corpus callosum, in the left striatal inferior frontal cortex and left superior corticostriate-parietal cortex only, in the foreceps major, foreceps minor and corpus callosum, and in the left superior corticostriate. And all these features found from interaction models were not shown at baseline. However, there is no result from anxiety group, depression group and somatic group, compared to controls. From these three diseases, we can find some features close to the reading line (p=0.05/6). From the correlation matrices, the imaging data showed different correlations between different groups in both baseline and longitudinal models except for structural MRI.
Conclusions:
In conclusion, we have discovered some important brain imaging indicators and brain areas in the development of ADHD, conduct, and oppositional defiant problems. At the same time, complex relationships between six diseases were found in different modalities. This will help to further understand the changes in the brain during the development of these diseases and can provide some new ideas for future intervention and treatment. Together, this has the potential to improve the treatment of children with mental health problems.
Disorders of the Nervous System:
Neurodevelopmental/ Early Life (eg. ADHD, autism) 1
Psychiatric (eg. Depression, Anxiety, Schizophrenia)
Modeling and Analysis Methods:
Activation (eg. BOLD task-fMRI) 2
Connectivity (eg. functional, effective, structural)
Diffusion MRI Modeling and Analysis
Keywords:
Anxiety
Data analysis
Development
Emotions
MRI
Psychiatric
Psychiatric Disorders
1|2Indicates the priority used for review
Provide references using author date format
1. Kessler, R.C., et al. Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey Replication. Archives of general psychiatry 62, 593-602 (2005).
2. Jernigan, T.L., Brown, S.A. & Dowling, G.J. The adolescent brain cognitive development study. Journal of research on adolescence: the official journal of the Society for Research on Adolescence 28, 154 (2018).
3. Krol, N.P., De Bruyn, E.E., Coolen, J.C. & van Aarle, E.J. From CBCL to DSM: a comparison of two methods to screen for DSM-IV diagnoses using CBCL data. Journal of Clinical Child and Adolescent Psychology 35, 127-135 (2006).
4. Hagler Jr, D.J., et al. Image processing and analysis methods for the Adolescent Brain Cognitive Development Study. Neuroimage 202, 116091 (2019).