Adult genomic medicine: lessons from a multisite study of 2700 patients
Bibliographic record
Abstract
BACKGROUND: Clinical exome and genome sequencing has transformed the diagnostic workup of patients with genetic disorders. The extensive body of evidence supporting the application of this clinical genomics approach in pediatric patients stands in stark contrast to the relative paucity of evidence for its use in the adult population. Here, we describe the largest cohort to date of adult patients who underwent clinical exome and genome sequencing for suspected genetic diagnoses. METHODS: A total of 2763 adult patients (2529 families) from all regions of Saudi Arabia are included in this cohort (2202 exomes, and 561 genomes). RESULTS: The diagnostic rate is 38.9% spanning 535 Mendelian genes and revealing clinical diagnostic errors in 38% of patients with positive reports. Structured feedback using C-GUIDE demonstrates clinical utility in 90% of positive cases. Consistent with the highly consanguineous nature of the local population, the majority (61%) of diagnosed phenotypes are recessive (94.6% homozygous) and founder variants account for 85% (414/487) of these variants. The same population characteristic has also led to the encounter of extremely rare, even novel recessive disorders including a highly penetrant novel RNF43-related hemochromatosis, NFXL1-related syndrome of hyperlaxity, short stature, and kidney disease, as well as autosomal recessive forms of typically dominant disorders. Multilocus phenotypes are observed in 5% of cases although only 26.7% of these are caused by two recessive variants. That 70% of molecular diagnoses encountered in our cohort are typically described in pediatric patients allowed us to observe highly unusual clinical presentations in the adult population. This delayed diagnosis also represents a missed opportunity for effective treatment in many instances and we note the availability of treatment for 26% of diagnosed conditions. Of particular interest are patients with monogenic disorders that could be overlooked as common multifactorial adult diseases (e.g., diabetes, dyslipidemia, stroke, chronic kidney disease, and dementia). Finally, we note the opportunities of deploying adult clinical genomics in an underrepresented population where 45.5% (373/819) of encountered variants are completely absent in gnomAD. CONCLUSIONS: Our results illustrate numerous benefits of a clinical genomics approach in adult medicine and argue for a broader implementation than currently practiced.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".