Project Summary Many people with autism spectrum disorder (ASD) are late- or never diagnosed (LDx). Initial data links female sex to LDx. Gender diversity is also overrepresented in ASD and associated with LDx. Autistic people assigned female at birth (ASDaF) and those who are gender diverse (ASDgd) experience increased psychiatric comorbidity, and, in the case of ASDgd, suicidality. LDx is associated with increased depression, anxiety and self-harm and limits access to supports, increasing vulnerability to abuse. Obstacles to timely diagnosis (Dx) of ASDaF may involve individual-level biobehavioral differences, including fewer unusual restricted/repetitive behaviors (RRBs), and strengths in social motivation, executive function and/or intelligence. Contextual factors, such as the predominance of young-cisgender-male conceptualizations of ASD in referral patterns and clinical diagnosis, also play a key role. Our goal is to integrate qualitative, quantitative, and artificial intelligence methods to identify contextual and biobehavioral predictors of LDx, leading to the development of a practicable screening measure for those at LDx risk. To illuminate mechanisms of LDx (1st ASD Dx > 12y) we will build on three legacies of our decade-long longitudinal ACE Network: 1) a sex-balanced, deeply phenotyped, longitudinal cohort of autistic youth & young adults; 2) a gender characterization method validated in ASD—the Gender Self-Report Scale (GSRS)—to quantify gender identity (binary and nonbinary) characteristics beyond assigned sex; and 3) a collaboration with autistic co-researchers to engage community-based participants to develop a self-report tool—the Self-Assessment of Autistic Traits (SAAT)—that captures the lived experience of ASD, including strengths. We will recruit a sex-balanced community-based sample of autistic people (ages 16-30y) to augment our longitudinal ACE cohort with two critical subgroups: LDx and ASDgd individuals. We will use intentional sampling and equitable inclusion across assigned sex, gender and gender diversity, ethno-racial identity, and LDx individuals with ASD. Using a mixed-methods approach, we will identify markers of LDx and examine the interplay between sex and gender in Dx timing and well-being outcomes. A sex, gender, and ethnoracially diverse stakeholder team of clinicians, self-advocates, autistic people, and parents, all with professional and/or lived experience with LDx ASD, will guide us as we: 1. Identify sex, gender, cognitive, and behavioral differences between timely (TDx) and LDx autistic people. 2. Develop and validate a self-report ASD screening measure as a diagnostic access point for adolescents/adults at risk for LDx. 3. Develop a personalized approach to biobehavioral marker extraction for classification of diagnostic timing (LDx vs. TDx) and prediction of QoL indices, using an innovative artificial intelligence approach to integrate multimodal neuroimaging data with phenotypic information. We will improve research and clinical practice by accelerating identification of adolescents and adults with ASD who have traditionally been missed or misdirected in the diagnostic process. This work will accelerate ASD Dx in the community, allowing for appropriate supports and improved outcomes.

Project Narrative Many female and gender diverse autistic people are late-, mis- or never diagnosed, putting them at greater risk for depression, anxiety and self-harm. We will tackle this problem and develop a tool to speed up diagnosis. This will help autistic people to get the right help at the right time, and improve quality of life.