Profiles in Nonverbal Learning Disability, Academic Skills, and Psychiatric Diagnoses in Children.

Importance: Nonverbal learning disability (NVLD) has been described since the 1960s, with varying subtypes proposed to address clinical heterogeneity. Objective: To identify profiles of NVLD to improve clinical practice and increase rigor in research by parsing clinical heterogeneity. Design, Setting, and Participants: This cross-sectional study used data from the Healthy Brain Network (HBN; release 8, years 2017 and 2021), a study of brain development and youth mental health that enrolls a community sample of New York, New York, children and adolescents (ages 5-21 years), to identify youths who met the research-defined criteria for NVLD. HBN recruits for desire to participate in research or perceived clinical concern, yielding a high proportion of youths with behavioral, learning, or emotional problems. An unsupervised clustering approach, Louvain community detection, was applied to the diagnostic parameters that defined NVLD. Profiles were described by patterns of strengths and weaknesses across diagnostic tests and by associations with clinical symptoms. Data were analyzed between April 22 and September 27, 2021. Exposure: Perceived clinical concern. Main Outcomes and Measures: The outcome of interest was NVLD profiles; hypotheses were generated prior to data analysis. Results: Among 1640 children and adolescents with complete data in the HBN, 180 participants (110 [61%] male; 86 participants [48%] age 10-14 years; range, 6-17 years) met the research criteria for NVLD. Four profiles emerged: profile 1 (44 children) included deficits in both dimensions of visual-spatial processing (mean [SD] Wechsler Visual-Spatial Index [VSI], 96.11 [11.91]; Fluid Reasoning Index [FRI], 77.18 [7.94]), highest inattention (mean [SD], 1.23 [1.05]]; P = .001) and aggression scores (mean [SD], 65.03 [15.89]; P = .001), and lowest reading comprehension scores (mean [SD], 93.81 [10.31]; P = .001); profile 2 (37 children) included deficits in VSI (mean [SD], 78.27 [13.55]) but not FRI, the highest math scores (mean [SD], 101.16 [17.57]; P = .001) and rate of anxiety disorder (odds ratio, 2.19; 95% CI, 1.31-3.66; P = .02), and the lowest rate of specific learning disorder (odds ratio, 0.20; 95% CI, 0.05-0.84; P = .01); profile 3 (35 children) included deficits in FRI (mean [SD], 88.6 [12.63]) and highest reading comprehension scores (mean [SD], 101.8 [14.12]; P < .001); profile 4 had no deficits in VSI or FRI, lowest verbal intelligence (mean [SD], 87.12 [13.07]; P = .001), and no functional impairments. In profiles with visual-spatial deficits (profiles 1, 2, and 3), VSI and FRI scores were positively associated with scores on measures of functional impairment, eg, FRI and math in profile 2 (Pearson r = .33; P < .001). Conclusions and Relevance: In this cross-sectional study of heterogeneity in NVLD, 3 profiles reflected NVLD and were differentially associated with psychiatric and academic outcomes. One profile (profile 4) showed no specific visual-spatial deficits and no associations between visual-spatial processing and functional domains, pointing to a need to consider a revision to the NVLD research criteria.