Subtyping attention-deficit/hyperactivity disorder using temperament dimensions: toward biologically based nosologic criteria

Abstract

Importance: Psychiatric nosology is limited by behavioral and biological heterogeneity within existing disorder categories. The imprecise nature of current nosologic distinctions limits both mechanistic understanding and clinical prediction. We demonstrate an approach consistent with the National Institute of Mental Health Research Domain Criteria initiative to identify superior, neurobiologically valid subgroups with better predictive capacity than existing psychiatric categories for childhood attention-deficit/hyperactivity disorder (ADHD).

Objective: To refine subtyping of childhood ADHD by using biologically based behavioral dimensions (i.e., temperament), novel classification algorithms, and multiple external validators.

Design, setting, and participants: A total of 437 clinically well-characterized, community-recruited children, with and without ADHD, participated in an ongoing longitudinal study. Baseline data were used to classify children into subgroups based on temperament dimensions and examine external validators including physiological and magnetic resonance imaging measures. One-year longitudinal follow-up data are reported for a subgroup of the ADHD sample to address stability and clinical prediction.

Main outcomes and measures: Parent/guardian ratings of children on a measure of temperament were used as input features in novel community detection analyses to identify subgroups within the sample. Groups were validated using 3 widely accepted external validators: peripheral physiological characteristics (cardiac measures of respiratory sinus arrhythmia and pre-ejection period), central nervous system functioning (via resting-state functional connectivity magnetic resonance imaging), and clinical outcomes (at 1-year longitudinal follow-up).

Results: The community detection algorithm suggested 3 novel types of ADHD, labeled as mild (normative emotion regulation), surgent (extreme levels of positive approach-motivation), and irritable (extreme levels of negative emotionality, anger, and poor soothability). Types were independent of existing clinical demarcations including DSM-5 presentations or symptom severity. These types showed stability over time and were distinguished by unique patterns of cardiac physiological response, resting-state functional brain connectivity, and clinical outcomes 1 year later.

Conclusions and relevance: Results suggest that a biologically informed temperament-based typology, developed with a discovery-based community detection algorithm, provides a superior description of heterogeneity in the ADHD population than does any current clinical nosologic criteria. This demonstration sets the stage for more aggressive attempts at a tractable, biologically based nosology.

Figure 1. Spring-embedded visualization of temperament groups

Graphical representation of the community detection results in the ADHD sample, which shows many strong correlations among individuals in the same temperament type and fewer between-type connections. Nodes represent individual’s in each temperament group (Blue: Mild, Red: Surgent, Green: Irritable) and connecting edges indicate correlations between individuals. (Note: Correlations are thresholded at .50 for purposes of visual representation; however, reported results are based on an unthresholded modularity algorithm as explained in Methods.)

Figure 2. Temperament type profiles

TMCQ scores for each of the three temperament types identified in the ADHD sample. Scores are shown as z-scores relative to the control sample mean (such that 0 on the Y axis is the mean of the typically-developing sample). Standard errors are shown. Scores were reversed for some scales as follows: for Inhibition high scores indicate less inhibitory control; for Attentional Focus, high scores mean poorer focus; for Shyness, high scores mean less shy; for Soothability, high scores indicate less soothabtility. Panel A) shows scores on temperament domains related to Cognitive Control; B) shows scores for Surgency domains; and C) shows scores for Negative Emotion Domains. Two scales that did not differentiate types (Openness and Perceptual Sensitivity) are not show, but scores for these scales are reported in eTable 2 in the Supplement.

Figure 3. Cardiac physiological response

A) Mean RSA change from baseline and B) raw PEP for each of the emotion task epochs: negative induction (NI), negative suppression (NS), positive induction (PI), and positive suppression (PS), shown by temperament type.

Figure 4. rs fcMRI conjunction maps

Amygdala connectivity maps for each temperament type were directly compared to the two other types and a matched control population. Results from each of these comparisons are provided in Table 1. The figure is a conjunction map for the comparisons. For each comparison (i.e. Mild vs Surgent, Mild vs Irritable, Mild vs Control – and similar for each of the two other subgroups), a voxel was coded as either 0 (not significantly different between groups) or 1 (significantly different between groups). Maps based on this coding were summed such that voxels that never differ between groups will have a value of 0 and voxels that differ in all comparisons for that group have a value of 3. In A) the Mild type differed from other types in areas in the posterior cingulate/precuneus (black arrow). B) As with the Mild type, the Surgent type also showed areas in the posterior cingulate and precuneus (black arrow) where it was distinct from at least 2 other groups. C) The Irritable type was quite distinct from Mild, Surgent, and control populations in the anterior insula (black arrows) – a region important for emotional regulation and task level control.