Development of polyphenotypic scores to prioritize detection of <i>G6PD</i> rs1050828-T carriers in African and African American populations
Bibliographic record
Abstract
Abstract Introduction The G6PD missense variant rs1050828-T is common in African and African American populations. It lowers HbA1c levels independent of glycemia, increasing the risk of underdiagnosis or delayed diagnosis of diabetes. We aimed to develop polyphenotypic scores (PPS) using routinely collected phenotypes to identify likely carriers. Materials and Methods Using data from 31,083 African or African American participants in the All of Us Research Program (AoU), we developed sex-specific PPS through multi-stage variable selection. We validated the PPS in independent African or African American individuals from AoU (N = 8,846), BioMe Biobank (N = 8,839), and UK Biobank (N = 6,811), and evaluated their utility among individuals without diagnosed diabetes. Results The PPS achieved an area under the receiver operating characteristic curve ranging from 0.7614 to 0.8686 in males and from 0.6033 to 0.6933 in females for identifying rs1050828-T carriers. Among individuals without diagnosed diabetes and with HbA1c <6.5%, PPS-based screening reduced the number needed to screen for identifying one carrier by 65-90% in males and 40-60% in females, compared to random screening. Discussion The PPS may help identify likely rs1050828-T carriers in African and African American populations, supporting prioritization for targeted genetic testing or alternative diagnostic approaches for diabetes.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".