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Getting the latest healthcare news for you
Researchers at UVA and Johns Hopkins have developed PGS-TRI, a statistical framework that separates the direct genetic effects on autism from the environmental influences parents create. Analyzing over 18,000 family trios, the tool confirmed the accuracy of existing genetic risk scores and flagged the CADM2 gene as a potential prevention target. It also found that maternal genetic traits like obesity may raise a child's autism risk.
Scientists at the University of Virginia and Johns Hopkins have unveiled PGS-TRI, a new statistical framework designed to disentangle the genetic and environmental contributors to autism. Unlike traditional genetic studies that focus solely on DNA passed from parent to child, PGS-TRI analyzes "case-parent trios" — data from a child and both parents — to distinguish between genes a child directly inherits and the environment parents genetically shape around them.
The tool was tested on more than 18,000 case-parent trios drawn from two major autism research consortia — SPARK and GEARS — spanning diverse ancestral populations. Results, published in Nature Genetics, validated existing polygenic risk scores for autism while also revealing important gaps: scores were more accurate for families of European, American, and South Asian ancestry than for those of African or East Asian descent, underscoring the need for greater diversity in genetic research.
Key Takeaways:
Why it matters: By mapping how both inherited genes and parent-created environments shape autism risk, PGS-TRI opens the door to more personalized, family-informed approaches to understanding and potentially preventing complex childhood developmental conditions.
