Overview: Research reports show that girls and boys show similar levels of concern for ASD and identify different biases that contribute to the inflated sex ratio for the diagnosis of autism. The findings may help early identification of girls on the autism spectrum.
Source: University of Minnesota
Published in Biological PsychiatryA multidisciplinary study led by the University of Minnesota showed that an equal number of girls and boys can be identified as people with autism spectrum disorder (ASD) when screened earlier, correcting large gender differences in current diagnoses.
“Conventional wisdom is that more boys than girls have ASD,” said study lead author Casey BurrowsPh.D., LP, an assistant professor at the University of Minnesota Medical School and a psychologist at M Health Fairview.
“Our research shows that girls and boys share the same level of concern about ASD and identifies some of the biases that contribute to inflated sex ratios. We hope this research will bring relief to women and girls who have struggled socially without knowing why.”
Using data from the Brain Imaging Research Network in Babiesthe study used a less biased sample that followed a group of children with a higher chance of developing ASD (eg, infant siblings of autistic children) aged six to 60 months.
The study found that an equal number of girls are identified with ASD-related concerns when children are screened early and when corrected for gender-based biases in diagnostic tools. This is in stark contrast to the current 4-to-1 sex ratio when following standard clinical referral processes.
“We know that the screening processes and diagnostic tools in ASD often miss many girls who later receive an ASD diagnosis,” said Dr. Burrows, who is also a member of the Freemason Institute for the Developing Brain†
“This prevents many girls from getting early intervention services at a time when they can have the most impact in early childhood. Most studies on ASD focus on children after they are diagnosed and lack information about symptoms in children that are missed by usual screening practices.”
The research team looked at whether girls and boys showed similar symptoms and found subtle differences in the structure of the core symptoms of ASD. After adjusting for these differences, the subgroup analysis identified a “of very high concern” group with a 1-to-1 male-to-female ratio.
“This approach — unbiased assessment, ensuring that our instruments measure what we think they measure — could help address current inequalities in the identification of autism,” he said. Jed ElisonPh.D., associate professor at the Institute of Child Development and Medical School and co-author of the paper.
“It is imperative to recognize and understand the limitations of traditional diagnostic and screening approaches and come up with creative solutions to identify all children who could benefit from early intervention services.”
Researchers plan to follow up on this work by examining the health of primary-to-secondary children in the high social care group. They also investigate group differences in underlying brain structure and function.
Financing: This study was supported by grants from the National Institutes of Health (R01-HD055741, R01-MH118362-01, R01-MH118362-02S1, U54-HD079124, P50-HD103573 (project ID 8084), U54-HD086984), Autism Speaks, and the Simon Foundation (140209). dr. Burrows was supported by an NIH Career Development Award (K12-HD055887).
About this autism research news
Author: Cat Dodge
Source: University of Minnesota
Contact: Kat Dodge – University of Minnesota
Image: The image is in the public domain
Original research: Closed access.
“A data-driven approach in an unbiased sample reveals an equivalent sex ratio of an autism spectrum disorder associated disorder in early childhood” by Casey Burrows et al. Biological Psychiatry
A data-driven approach in an unbiased sample reveals an equivalent sex ratio of an autism spectrum disorder associated disorder in early childhood
Sex differences in the prevalence of neurodevelopmental disorders are especially evident in autism spectrum disorder (ASD). Heterogeneous symptom presentation and the potential of measurement bias hinder early ASD detection in women and may contribute to discrepant prevalence estimates. We examined trajectories of social communication (SC) and restricted and repetitive behaviors (RRBs) in a sample of infant siblings of autistic children, adjusted for age- and gender-based measurement bias. We hypothesized that using a prospective increased familial probability sample, deriving data-driven behavioral constructs, and taking measurement bias into account would reveal less discrepant sex ratios than typically seen in ASD.
We performed direct assessments of ASD symptoms at ages 6-9, 12-15, 24, and 36-60 months (total Nobservations=1254) with young siblings of autistic children (N=377) and a comparison group with a lower ASD familial probability (N=168; Nobservations=527). We established measurement invariance across age and gender for separate models of SC and RRB. We then performed latent class growth mixture modeling with the longitudinal data and evaluated for gender differences in trajectory membership.
We identified two latent classes in the SC and RRB models with equal sex ratios in the cluster of concern for both SC and RRB. Sex differences were also observed in the high-concern SC cluster, indicating that girls classified as “heightened social concerns” show milder symptoms than boys in this group.
This novel approach for characterizing the progression of ASD symptoms emphasizes the utility of assessing and adjusting sex-related measurement biases and identifying gender-specific patterns of symptom onset.