Inbreeding, Native American ancestry and child mortality: linking human selection and paediatric medicine
Bibliographic record
Abstract
The children of related parents show increased risk of early mortality. The Native American genome typically exhibits long stretches of homozygosity, and Latin Americans are highly heterogeneous regarding the individual burden of homozygosity, the proportion and the type of Native American ancestry. We analysed nationwide mortality and genome-wide genotype data from admixed Chileans to investigate the relationship between common causes of child mortality, homozygosity and Native American ancestry. Results from two-stage linear-Poisson regression revealed a strong association between the sum length of runs of homozygosity (SROH) above 1.5 Megabases (Mb) in each genome and mortality due to intracranial non-traumatic haemorrhage of foetus and newborn (5% increased risk of death per Mb in SROH, P = 1 × 10-3) and disorders related to short gestation and low birth weight (P = 3 × 10-4). The major indigenous populations in Chile are Aymara-Quechua in the north of the country and the Mapuche-Huilliche in the south. The individual proportion of Aymara-Quechua ancestry was associated with an increased risk of death due to anencephaly and similar malformations (P = 4 × 10-5), and the risk of death due to Edwards and Patau trisomy syndromes decreased 4% per 1% Aymara-Quechua ancestry proportion (P = 4 × 10-4) and 5% per 1% Mapuche-Huilliche ancestry proportion (P = 2 × 10-3). The present results suggest that short gestation, low birth weight and intracranial non-traumatic haemorrhage mediate the negative effect of inbreeding on human selection. Independent validation of the identified associations between common causes of child death, homozygosity and fine-scale ancestry proportions may inform paediatric medicine.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".