Latest Autism Research Findings 2025: What Families Need to Know

What autism research is currently going on?

The short answer: a lot. And it’s changing fast. From biomarker breakthroughs and AI screening tools to personalized subtypes and large-scale data projects, 2025 has been a defining year.

In ABA Centers of Delaware, we understand the need to keep up with the latest autism research among parents and caregivers of neurodivergent children, because this represents hope. For families, educators, and clinicians, each discovery opens another door to understanding, inclusion, and better outcomes for people with autism.

In 2025, significant updates from organizations are shaping how we view diagnosis, treatment, and the future of neurodiversity. For example, a recent report from HHS revealed that autism diagnoses have risen to 1 in 31 children, sparking both concern and curiosity. What’s behind this jump? Are we facing an “autism epidemic,” or simply becoming better at recognizing it?

Keep reading this article by ABA Centers of Delaware, where we explore what these findings really mean for families and the autism community.

Key Shifts in Autism Prevalence & Epidemiology

According to the CDC, autism prevalence has increased from 1 in 36 children in 2020 to 1 in 31 in 2025. The HHS report called it an “autism epidemic.” Still, experts emphasize that the rise reflects a mix of factors like better awareness, earlier screening, and broader diagnostic criteria, rather than a true surge in cases.

This update is one of the biggest takeaways in new autism research: our improved understanding of developmental differences is helping identify children sooner, including girls and those from diverse backgrounds who were often overlooked in the past.

However, these numbers also highlight an urgent need for support. As prevalence rises, so does the importance of accessible intervention, education, and family guidance. Here is where behavioral health providers and ABA therapy play a crucial role.

Biomarkers, AI & New Tools in Autism Diagnosis

One of the most exciting developments in autism research comes from the intersection of biology and technology. Scientists are discovering biomarkers, biological indicators that can help detect autism earlier and more accurately.

A CAS Insights study reported significant progress in identifying these biomarkers, such as unique patterns in eye-tracking, facial expressions, and even saliva samples. These biological clues could soon complement behavioral assessments, offering more objective insights into autism diagnosis.

Meantime, the National Institute of Mental Health (NIMH) is supporting a digital autism screening tool that uses AI and machine learning to analyze children’s speech, movement, and play behaviors. During routine doctor visits, toddlers watched short videos while the app’s camera recorded their behaviors, eye contact, facial expressions, head movements, and reactions to their name.

Using AI and machine learning, the app analyzed these behaviors to predict autism likelihood and ensure test accuracy. Involving 475 toddlers aged 17–36 months, the study found the app could distinguish between children later diagnosed with autism and those with other developmental or language delays, suggesting it could be a fast, accessible tool for early autism detection.

This new autism research signals a shift toward precision diagnostics, where biological and behavioral data work hand in hand. It’s a hopeful sign for families who have long faced delays in getting answers.

Distinct Autism Subtypes & Personalized Approaches

A groundbreaking study by Nature Genetics identified biologically distinct autism subtypes, each with its own genetic and neurological signatures.

The researchers analyzed detailed behavioral data from over 5,000 individuals with ASD. They used a statistical method that grouped them into four distinct classes based on patterns across many traits (social behavior, repetitive behaviors, developmental delay, etc.). Each class had a different “profile” of symptoms, co-occurring conditions, and genetic signatures. For example:

• Social/behavioral: Strong differences in social or behavioral symptoms but fewer developmental delays; more linked to common genetic variation tied to ADHD and depression, and later-expressed genes.
• Mixed ASD with DD: Notable developmental delays plus autism traits; enriched in both rare inherited and de novo (new) variants, especially in genes active early in brain development.
• Moderate challenges: Milder overall symptoms; genetic changes tended to affect genes with lower evolutionary constraint.
• Broadly affected: The most severe across many domains (development, cognition, behavior); highest burden of de novo mutations in highly constrained genes, including those targeted by FMRP (a protein essential for neural regulation).