Evolution of Lactase Persistence: Turbo-Charging Adaptation in Growth Under the Selective Pressure of Maternal Mortality?
Bibliographic record
Abstract
The emergence of the capacity to digest milk in some populations represents a landmark in human evolution, linking genetic change with a component of niche construction, namely dairying. Alleles promoting continued activity of the enzyme lactase through the life-course (lactase persistence) evolved in several global regions within the last 7,000 years. In some European regions, these alleles underwent rapid selection and must have profoundly affected fertility or mortality. Elsewhere, alleles spread more locally. However, the functional benefits underlying the rapid spread of lactase persistence remain unclear. Here, we set out the hypothesis that lactase persistence promoted skeletal growth, thereby offering a generic rapid solution to childbirth complications arising from exposure to ecological change, or to new environments through migration. Since reduced maternal growth and greater neonatal size both increase the risk of obstructed labour, any ecological exposure impacting these traits may increase maternal mortality risk. Over many generations, maternal skeletal dimensions could adapt to new ecological conditions through genetic change. However, this adaptive strategy would fail if ecological change was rapid, including through migration into new niches. We propose that the combination of consuming milk and lactase persistence could have reduced maternal mortality by promoting growth of the pelvis after weaning, while high calcium intake would reduce risk of pelvic deformities. Our conceptual framework provides locally relevant hypotheses to explain selection for lactase persistence in different global regions. For any given diet and individual genotype, the combination of lactase persistence and milk consumption would divert more energy to skeletal growth, either increasing pelvic dimensions or buffering them from worsening ecological conditions. The emergence of lactase persistence among dairying populations could have helped early European farmers adapt rapidly to northern latitudes, East African pastoralists adapt to sudden climate shifts to drier environments, and Near Eastern populations counteract secular declines in height associated with early agriculture. In each case, we assume that lactase persistence accelerated the timescale over which maternal skeletal dimensions could change, thus promoting both maternal and offspring survival. Where lactase persistence did not emerge, birth weight was constrained at lower levels, and this contributes to contemporary variability in diabetes risk.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".