Irritability is present in multiple disorders in youth, suggesting that it is a dimension of psychopathology that cuts across traditional categorical diagnostic boundaries. We propose to investigate how abnormal brain development produces dimensionally defined symptoms of irritability by leveraging the resources and data of the Philadelphia Neurodevelopmental Cohort (PNC). As part of the PNC, a large sample (n=1,601) of youth ages 8-21 completed cross-sectional neuroimaging along with clinical and cognitive phenotyping, including screening questions for irritability. We will conduct longitudinal follow-up multi-modal neuroimaging in 140 youth with diverse psychopathology who screened positive for symptoms of irritability, as well as 60 matched typically developing controls. We will repeat the imaging sequences performed at baseline including T1 imaging of brain structure, arterial spin labeled MRI of cerebral perfusion, a resting-state scan of functional connectivity, and a fractal version of the n-back working memory task. These longitudinal measures will be supplemented by the cross-sectional acquisition of sequences that are particularly relevant to irritability, including a high temporal resolution resting state sequence to examine dynamic executive-affective connectivity as well as a social affective feedback fMRI paradigm that recruits both the ventral striatum and the amygdala. The comprehensive assessment of brain structure and function provided by these measures will enable testing a model which posits that irritability results an evolving combination of executive deficits, affective dysregulation, and executive-affective dysconnectivity. Accordingly, in Aim 1 we will delineate how longitudinal changes in brain development as measured by multi-modal imaging are associated with irritability.
In Aim 2, we will demonstrate that irritability is associated abnormal affective activation and connectivity using specialized functional imaging sequences acquired at follow-up.
In Aim 3, as prior work has demonstrated sex differences in the both irritability and patterns of brain development, we will examine how brain phenotypes associated with irritability differ by sex. Finally, in Exploratory Aim 4 we will use advanced multivariate pattern analysis techniques to integrate high-dimensional multi-modal imaging data and predict irritability. This application capitalizes on the PI's clinical experience, expertise in multi-modal developmental neuroimaging, established collaborations, and intimate familiarity with the PNC dataset. Through the proposed multi-level analysis, this innovative research will provide a substantial advance in our understanding of the neurodevelopmental substrates of irritability.

Public Health Relevance

Irritability is a debilitating dimension of psychopathology that is present in multiple psychiatric disorders. Greater understanding of how abnormalities in brain development during youth produce symptoms of irritability may be critical for the development of earlier and more effective treatments. This would benefit public health by reducing the great costs of irritability to individuals and society at large.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
1R01MH107703-01
Application #
8956455
Study Section
Special Emphasis Panel (ZMH1)
Program Officer
Garriock, Holly A
Project Start
2015-09-01
Project End
2019-05-31
Budget Start
2015-09-01
Budget End
2016-05-31
Support Year
1
Fiscal Year
2015
Total Cost
Indirect Cost
Name
University of Pennsylvania
Department
Psychiatry
Type
Schools of Medicine
DUNS #
042250712
City
Philadelphia
State
PA
Country
United States
Zip Code
19104
Reardon, P K; Seidlitz, Jakob; Vandekar, Simon et al. (2018) Normative brain size variation and brain shape diversity in humans. Science 360:1222-1227
Pehlivanova, Marieta; Wolf, Daniel H; Sotiras, Aristeidis et al. (2018) Diminished Cortical Thickness is Associated with Impulsive Choice in Adolescence. J Neurosci :
Medaglia, John D; Satterthwaite, Theodore D; Kelkar, Apoorva et al. (2018) Brain state expression and transitions are related to complex executive cognition in normative neurodevelopment. Neuroimage 166:293-306
Papadopoulos, Lia; Blinder, Pablo; Ronellenfitsch, Henrik et al. (2018) Comparing two classes of biological distribution systems using network analysis. PLoS Comput Biol 14:e1006428
Alexander-Bloch, Aaron F; Shou, Haochang; Liu, Siyuan et al. (2018) On testing for spatial correspondence between maps of human brain structure and function. Neuroimage 178:540-551
Braun, Urs; Schaefer, Axel; Betzel, Richard F et al. (2018) From Maps to Multi-dimensional Network Mechanisms of Mental Disorders. Neuron 97:14-31
Kaczkurkin, A N; Moore, T M; Calkins, M E et al. (2018) Common and dissociable regional cerebral blood flow differences associate with dimensions of psychopathology across categorical diagnoses. Mol Psychiatry 23:1981-1989
Baum, Graham L; Roalf, David R; Cook, Philip A et al. (2018) The impact of in-scanner head motion on structural connectivity derived from diffusion MRI. Neuroimage 173:275-286
Muldoon, Sarah F; Costantini, Julia; Webber, W R S et al. (2018) Locally stable brain states predict suppression of epileptic activity by enhanced cognitive effort. Neuroimage Clin 18:599-607
Li, Hongming; Satterthwaite, Theodore D; Fan, Yong (2018) BRAIN AGE PREDICTION BASED ON RESTING-STATE FUNCTIONAL CONNECTIVITY PATTERNS USING CONVOLUTIONAL NEURAL NETWORKS. Proc IEEE Int Symp Biomed Imaging 2018:101-104

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