TY - JOUR
T1 - Integrating causal discovery and clinically-relevant insights to explore directional relationships between autistic features, sex at birth, and cognitive abilities
AU - Tseng, Angela
AU - Francis, Sunday M.
AU - Rawls, Eric
AU - Conelea, Christine
AU - Grissom, Nicola M.
AU - Kummerfeld, Erich
AU - Ma, Sisi
AU - Jacob, Suma
N1 - Publisher Copyright:
© The Author(s), 2025. Published by Cambridge University Press.
PY - 2025/3/18
Y1 - 2025/3/18
N2 - Background Access to big data is a boon for researchers, fostering collaboration and resource-sharing to accelerate advancements across fields. Yet, disentangling complex datasets has been hindered by methodological limitations, calling for alternative, interdisciplinary approaches to parse manifold multi-directional pathways between clinical features, particularly for highly heterogeneous autism spectrum disorder (ASD). Despite a long history of male-bias in ASD prevalence, no consensus has been reached regarding mechanisms underlying sex-related discrepancies. Methods Applying a novel network-theory-based approach, we extracted data-driven, clinically-relevant insights from a well-characterized sample (http://sfari.org/simons-simplex-collection) of autistic males (N = 2175, Age = 8.9 ± 3.5 years) and females (N = 334, Age = 9.2 ± 3.7 years). Expert clinical review of exploratory factor analysis (EFA) results yielded factors of interest in sensory, social, and restricted and repetitive behavior domains. To offset inherent confounds of sample imbalance, we identified a comparison subgroup of males (N = 331) matched to females (by age, IQ). We applied data-driven causal discovery analysis (CDA) using Greedy Fast Causal Inference (GFCI) on three groups (all females, all males, matched males). Structural equation modeling (SEM) extracted measures of model-fit and effect sizes for causal relationships between sex, age-at-enrollment, and IQ on EFA-determined factors. Results We identified potential targets for intervention at nodes with mediating or indirect effects. For example, in the female and matched male groups, analyses suggest mitigating RRB domain behaviors may lead to downstream reductions in oppositional and self-injurious behaviors. Conclusions Our investigation unveiled sex-specific directional relationships that inform our understanding of differing needs and outcomes associated with biological sex in autism and may serve to further development of targeted interventions.
AB - Background Access to big data is a boon for researchers, fostering collaboration and resource-sharing to accelerate advancements across fields. Yet, disentangling complex datasets has been hindered by methodological limitations, calling for alternative, interdisciplinary approaches to parse manifold multi-directional pathways between clinical features, particularly for highly heterogeneous autism spectrum disorder (ASD). Despite a long history of male-bias in ASD prevalence, no consensus has been reached regarding mechanisms underlying sex-related discrepancies. Methods Applying a novel network-theory-based approach, we extracted data-driven, clinically-relevant insights from a well-characterized sample (http://sfari.org/simons-simplex-collection) of autistic males (N = 2175, Age = 8.9 ± 3.5 years) and females (N = 334, Age = 9.2 ± 3.7 years). Expert clinical review of exploratory factor analysis (EFA) results yielded factors of interest in sensory, social, and restricted and repetitive behavior domains. To offset inherent confounds of sample imbalance, we identified a comparison subgroup of males (N = 331) matched to females (by age, IQ). We applied data-driven causal discovery analysis (CDA) using Greedy Fast Causal Inference (GFCI) on three groups (all females, all males, matched males). Structural equation modeling (SEM) extracted measures of model-fit and effect sizes for causal relationships between sex, age-at-enrollment, and IQ on EFA-determined factors. Results We identified potential targets for intervention at nodes with mediating or indirect effects. For example, in the female and matched male groups, analyses suggest mitigating RRB domain behaviors may lead to downstream reductions in oppositional and self-injurious behaviors. Conclusions Our investigation unveiled sex-specific directional relationships that inform our understanding of differing needs and outcomes associated with biological sex in autism and may serve to further development of targeted interventions.
KW - Autism
KW - Causal Discovery Analysis
KW - Cognitive
KW - Restricted and Repetitive Behaviors (RRBs)
KW - Sex Differences
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U2 - 10.1017/S0033291725000571
DO - 10.1017/S0033291725000571
M3 - Article
C2 - 40098476
AN - SCOPUS:105000700384
SN - 0033-2917
VL - 55
JO - Psychological medicine
JF - Psychological medicine
M1 - e89
ER -