Diagnostic Yield and Clinical Actionability of Genetic Testing in Neurodevelopmental Disorders: A Systematic Review...

Genetic testing is increasingly central to the evaluation of neurodevelopmental disorders (NDDs), yet most evidence emphasises diagnostic yield rather than whether findings change clinical care. We conducted a systematic review and meta-analysis (Preferred Reporting Items for Systematic Reviews and Meta-Analyses [PRISMA] 2020) of genetic testing across the diagnostic pathway in NDD populations, focusing on autism spectrum disorder (ASD), intellectual disability, and global developmental delay, to quantify pooled diagnostic yield and clinical actionability. A systematic search of PubMed and Web of Science, with an expanded population and outcome term set, was completed on 1 October 2026, supplemented by an artificial intelligence (AI)-assisted search (Undermind) and reference-list screening. Twenty-three studies were included in a qualitative synthesis and 22 in a quantitative meta-analysis of diagnostic yield (N = 7641 patients tested; diagnostic-yield analysis comprised 23 data points, as Charouf et al. contributed separate whole-exome sequencing (WES) and whole-genome sequencing (WGS) cohorts). Single-proportion random-effects meta-analysis with the Freeman-Tukey double arcsine transformation produced a pooled diagnostic yield of 28% (95% confidence interval [CI] 21-35%; I² = 96.1%) and pooled clinical actionability of 58% (95% CI 44-72%; I² = 95.7%) across 16 studies (N = 1538 patients with confirmed diagnoses). A significant yield gradient was observed across modalities (chromosomal microarray analysis [CMA], 16%; WES, 36%; WGS, 43%; p < 0.0001). Actionability estimates were robust across sensitivity analyses (54-64%). Genetic testing in NDDs functions not only as an etiological tool but as an input to personalised management, including pharmacological optimisation, comorbidity surveillance, and resolution of the diagnostic odyssey, albeit with very low certainty of evidence per Grading of Recommendations, Assessment, Development and Evaluations (GRADE), reflecting substantial heterogeneity and observational study design.