Genetic testing for diagnosing neurodevelopmental disorders and epilepsy: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Identifying the genetic causes of neurodevelopmental disorders (NDDs) and epilepsy is crucial for effective treatment and genetic counseling. Our objective was to determine the diagnostic yield of chromosomal microarray (CMA) and next-generation sequencing (NGS) methods-including targeted sequencing (TS), whole-exome sequencing (WES), and whole-genome sequencing (WGS)-in individuals with NDDs or epilepsy. METHODS: We systematically searched PubMed, Embase, and the Cochrane Library through August 31, 2024. Two reviewers independently screened studies and extracted data. We included studies with ≥ 10 patients (probands) diagnosed with an NDD or epilepsy who underwent CMA, TS, WES, WGS, or WES reanalysis. Methodological quality was assessed using the Newcastle-Ottawa Scale (NOS). Random-effects meta-analysis was performed to pool diagnostic yield percentages. Subgroup analyses were conducted by test modality, disorder subtype, and clinical features. RESULTS: A total of 416 studies (124,937 participants) met inclusion criteria. Pooled analysis showed significantly higher diagnostic yields with NGS methods compared to CMA (31.1% vs 14.8% in NDD cohorts; 28.7% vs 13.3% in epilepsy cohorts). Within NGS, WES had a higher yield than targeted gene panels (35.3% vs. 23.2% for NDDs; 34.2% vs. 24.0% for epilepsy). Diagnostic yields increased over time in more recent studies. Patients with certain clinical features had particularly high yields: NDDs with dysmorphic features (54.7%), syndromic presentations (37.6%), or co-occurring epilepsy (35.6%), and epilepsy with early onset (32.3%), epileptic encephalopathy (34.7%), or drug-resistant seizures (25.4%). Quality assessment using NOS revealed that the majority of included studies were of good to very good methodological quality. CONCLUSIONS: Despite substantial between-study heterogeneity and variability in study designs that may limit the certainty of our pooled estimates, and potential publication bias, our results demonstrate that NGS-based tests-particularly WES and WGS-provide markedly higher diagnostic yields in patients with NDDs or epilepsy compared to CMA, supporting their use as first-line genetic tests. Patients with dysmorphism, syndromic NDD, early-onset or refractory epilepsy, and epileptic encephalopathy achieve above-average diagnostic yields, highlighting the value of comprehensive genetic testing in these subgroups. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42024555664.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.013 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".