Genetics of metabolic traits in Greenlanders: lessons from an isolated population
Bibliographic record
Abstract
In this review, we describe the extraordinary population of Greenland, which differs from large outbred populations of Europe and Asia, both in terms of population history and living conditions. Many years in isolation, small population size and an extreme environment have shaped the genetic composition of the Greenlandic population. The unique genetic background combined with the transition from a traditional Inuit lifestyle and diet, to a more Westernized lifestyle, has led to an increase in the prevalence of metabolic conditions like obesity, where the prevalence from 1993 to 2010 has increased from 16.4% to 19.4% among men, and from 13.0% to 25.4% among women, type 2 diabetes and cardiovascular diseases. The genetic susceptibility to metabolic conditions has been explored in Greenlanders, as well as other isolated populations, taking advantage of population-genetic properties of these populations. During the last 10 years, these studies have provided examples of loci showing evidence of positive selection, due to adaption to Arctic climate and Inuit diet, including TBC1D4 and FADS/CPT1A, and have facilitated the discovery of several loci associated with metabolic phenotypes. Most recently, the c.2433-1G>A loss-of-function variant in ADCY3 associated with obesity and type 2 diabetes was described. This locus has provided novel biological insights, as it has been shown that reduced ADCY3 function causes obesity through disrupted function in primary cilia. Future studies of isolated populations will likely provide further genetic as well as biological insights.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".