# Autism Center of Excellence Network: Neurodevelopmental Biomarkers of Late Diagnosis in Female and Gender Diverse Autism

> **NIH NIH R01** · UNIVERSITY OF VIRGINIA · 2022 · $2,558,232

## Abstract

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...

## Key facts

- **NIH application ID:** 10531482
- **Project number:** 2R01MH100028-12
- **Recipient organization:** UNIVERSITY OF VIRGINIA
- **Principal Investigator:** Allison Elizabeth Jack
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $2,558,232
- **Award type:** 2
- **Project period:** 2012-09-04 → 2027-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10531482

## Citation

> US National Institutes of Health, RePORTER application 10531482, Autism Center of Excellence Network: Neurodevelopmental Biomarkers of Late Diagnosis in Female and Gender Diverse Autism (2R01MH100028-12). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10531482. Licensed CC0.

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