Whole genome sequencing (WGS) identified clinically significant genetic variants in approximately one in eight children with cerebral palsy in a UK pilot study, with every confirmed diagnosis influencing patient care or genetic counselling.
Published in The Lancet Regional Health – Europe, the research provides evidence supporting the use of genomic testing in NHS assessments of children with cerebral palsy.
Although cerebral palsy has traditionally been associated with brain injury during pregnancy, birth, or early infancy, growing evidence suggests that some affected children have underlying genetic conditions.
Researchers led by the University of Cambridge recruited 86 children with cerebral palsy from five NHS specialist clinics in England. Participants underwent WGS, usually alongside their biological parents, with artificial intelligence (AI) software used to prioritize potentially disease-causing variants.
Pathogenic or likely pathogenic variants were identified in 11 children (12.8 percent). Another eight (9.3 percent) carried variants considered potentially relevant but insufficient to establish a diagnosis.
The confirmed genetic findings influenced care in all 11 cases. Four children received tailored clinical management, while seven required additional specialist care.
Examples included changing antiseizure medication following identification of an SCN1A variant, arranging specialist mitochondrial assessment, and introducing cardiovascular screening after detection of a COL4A1 variant.
Genetic diagnoses also provided information about prognosis and the likelihood of recurrence in future pregnancies.
For genomic laboratories, the findings demonstrate the value of combining broad genome analysis with targeted gene lists and multidisciplinary variant interpretation. Several diagnostic variants would have been missed by restricting analysis to genes already associated with cerebral palsy.
The researchers also developed a machine learning model using standardized clinical descriptions to identify children more likely to receive a genetic diagnosis. The model achieved an area under the curve of 0.88, suggesting potential for improving testing decisions.
Intellectual disability, dystonia, and abnormalities affecting multiple body systems were associated with greater diagnostic probability.
The findings support considering WGS within cerebral palsy diagnostic pathways, particularly when additional clinical features suggest an underlying genetic condition.
However, the small study population and substantial number of uncertain findings highlight the need for larger prospective studies to establish diagnostic effectiveness, cost-effectiveness, and appropriate patient selection.
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