# Evaluating ASD Symptomatology in Children with Down Syndrome

> **NIH NIH R21** · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · 2021 · $440,823

## Abstract

PROJECT SUMMARY/ABSTRACT
 Approximately 1 in 5 individuals with Down syndrome (DS) meet criteria for comorbid autism spectrum
disorder (ASD), a tenfold increase in risk compared to the general population. Comorbid ASD is associated with
delayed language, increased behavioral challenges, greater demands on caregivers, and higher costs of
healthcare across the lifespan. Recent advances in precision medicine have the potential to substantially
improve long-term outcomes among individuals with DS and comorbid conditions such as ASD. However, for
this potential to be realized, reliable and valid measures are required. There is currently little scientific basis for
the identification and measurement of ASD symptoms in DS. Without accurate measurement, clinical trials in
DS cannot properly apply ASD inclusion criteria, stratify cohorts where necessary, or track response to treatment.
Consequently, there is an urgent need for clinical trials to have reliable, valid ASD screening, diagnostic, and
symptom monitoring tools in DS. To address this need, we propose to (1) evaluate the psychometric
characteristics of ASD symptom measures in DS, and (2) characterize ASD symptom profiles in DS through
deep phenotyping. Characterizing ASD symptoms and related developmental features in DS will further inform
clinical trials by enabling them to stratify cohorts by comorbid ASD and monitor response to treatment across
symptom profiles. These aims align with two priorities of the NIH INCLUDE Project: (a) increase the likelihood
of clinical trial success through testing of clinical outcome assessment measures, and (b) define the presentation
and course of co-occurring conditions in individuals with DS. In an effort to improve the efficiency, generalizability,
and inclusiveness of future clinical trials, the proposed study will be conducted online. To accomplish these aims,
we will leverage existing resources (NIH’s DS-Connect; Emory University’s DS360) to conduct a large-scale,
nationwide study of ASD symptoms in 500 6- to 18-year-olds with DS. We will examine the reliability, validity,
and variability of three well-known caregiver report-based ASD screening and symptom measures. We will
leverage data from these ASD measures, along with additional deep phenotyping, to characterize the
heterogeneity of the ASD phenotype in DS and identify symptom profiles. Finally, we propose an exploratory aim
among a subsample (n = 25) at high or low ASD risk to examine the feasibility of tele-assessment methods for
gathering direct, performance-based ASD evaluations. Data generated from this project will enhance clinical trial
readiness by providing ASD measures in DS that can (a) screen for ASD risk to identify candidates for treatment
and (b) stratify cohorts by ASD symptom profiles and monitor response to treatment across these profiles. Once
validated, these ASD measures will provide a much-needed resource for future clinical trials to document
outcomes in response to treatment. ...

## Key facts

- **NIH application ID:** 10294431
- **Project number:** 1R21HD106125-01
- **Recipient organization:** UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN
- **Principal Investigator:** Marie Moore Channell
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $440,823
- **Award type:** 1
- **Project period:** 2021-09-09 → 2025-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10294431

## Citation

> US National Institutes of Health, RePORTER application 10294431, Evaluating ASD Symptomatology in Children with Down Syndrome (1R21HD106125-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10294431. Licensed CC0.

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