Insulin Sensitivity and Insulin Clearance Are Heritable and Have Strong Genetic Correlation in Mexican Americans
Bibliographic record
Abstract
OBJECTIVE: The GUARDIAN (Genetics UndeRlying DIAbetes in HispaNics) consortium is described, along with heritability estimates and genetic and environmental correlations of insulin sensitivity and metabolic clearance rate of insulin (MCRI). METHODS: GUARDIAN is comprised of seven cohorts, consisting of 4,336 Mexican-American individuals in 1,346 pedigrees. Insulin sensitivity (SI ), MCRI, and acute insulin response (AIRg) were measured by frequently sampled intravenous glucose tolerance test in four cohorts. Insulin sensitivity (M, M/I) and MCRI were measured by hyperinsulinemic-euglycemic clamp in three cohorts. Heritability and genetic and environmental correlations were estimated within the family cohorts (totaling 3,925 individuals) using variance components. RESULTS: Across studies, age, and gender-adjusted heritability of insulin sensitivity (SI , M, M/I) ranged from 0.23 to 0.48 and of MCRI from 0.35 to 0.73. The ranges for the genetic correlations were 0.91 to 0.93 between SI and MCRI; and -0.57 to -0.59 for AIRg and MCRI (all P < 0.0001). The ranges for the environmental correlations were 0.54 to 0.74 for SI and MCRI (all P < 0.0001); and -0.16 to -0.36 for AIRg and MCRI (P < 0.0001-0.06). CONCLUSIONS: These data support a strong familial basis for insulin sensitivity and MCRI in Mexican Americans. The strong genetic correlations between MCRI and SI suggest common genetic determinants.
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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 | 0.003 |
| 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 | 0.001 | 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".