Genetic and metabolic investigations for neurodevelopmental disorders: position statement of the Canadian College of Medical Geneticists (CCMG)
Bibliographic record
Abstract
PURPOSE AND SCOPE: The aim of this position statement is to provide recommendations for clinicians regarding the use of genetic and metabolic investigations for patients with neurodevelopmental disorders (NDDs), specifically, patients with global developmental delay (GDD), intellectual disability (ID) and/or autism spectrum disorder (ASD). This document also provides guidance for primary care and non-genetics specialists caring for these patients while awaiting consultation with a clinical geneticist or metabolic specialist. METHODS OF STATEMENT DEVELOPMENT: A multidisciplinary group reviewed existing literature and guidelines on the use of genetic and metabolic investigations for the diagnosis of NDDs and synthesised the evidence to make recommendations relevant to the Canadian context. The statement was circulated for comment to the Canadian College of Medical Geneticists (CCMG) membership-at-large and to the Canadian Pediatric Society (Mental Health and Developmental Disabilities Committee); following incorporation of feedback, it was approved by the CCMG Board of Directors on 1 September 2022. RESULTS AND CONCLUSIONS: Chromosomal microarray is recommended as a first-tier test for patients with GDD, ID or ASD. Fragile X testing should also be done as a first-tier test when there are suggestive clinical features or family history. Metabolic investigations should be done if there are clinical features suggestive of an inherited metabolic disease, while the patient awaits consultation with a metabolic physician. Exome sequencing or a comprehensive gene panel is recommended as a second-tier test for patients with GDD or ID. Genetic testing is not recommended for patients with NDDs in the absence of GDD, ID or ASD, unless accompanied by clinical features suggestive of a syndromic aetiology or inherited metabolic disease.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.033 | 0.099 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.029 | 0.028 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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 source (direct Gemma or distilled Codex), 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".