Genetic architecture and adaptations of Nunavik Inuit
Bibliographic record
Abstract
The Canadian Inuit have a distinct population background that may entail particular implications for the health of its individuals. However, the number of genetic studies examining this Inuit population is limited, and much remains to be discovered in regard to its genetic characteristics. In this study, we generated whole-exome sequences and genomewide genotypes for 170 Nunavik Inuit, a small and isolated founder population of Canadian Arctic indigenous people. Our study revealed the genetic background of Nunavik Inuit to be distinct from any known present-day population. The majority of Nunavik Inuit show little evidence of gene flow from European or present-day Native American peoples, and Inuit living around Hudson Bay are genetically distinct from those around Ungava Bay. We also inferred that Nunavik Inuit have a small effective population size of 3,000 and likely split from Greenlandic Inuit ∼10.5 kya. Nunavik Inuit went through a bottleneck at approximately the same time and might have admixed with a population related to the Paleo-Eskimos. Our study highlights population-specific genomic signatures in coding regions that show adaptations unique to Nunavik Inuit, particularly in pathways involving fatty acid metabolism and cellular adhesion ( CPNE7 , ICAM5 , STAT2 , and RAF1 ). Subsequent analyses in selection footprints and the risk of intracranial aneurysms (IAs) in Nunavik Inuit revealed an exonic variant under weak negative selection to be significantly associated with IA (rs77470587; P = 4.6 × 10 −8 ).
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".