Genetic variation in the sucrase‐isomaltase ( <i>SI)</i> gene is associated with dietary intake in a young adult population
Bibliographic record
Abstract
Background Genetic variation contributes to individual differences in energy and nutrient intake and may be a contributing factor to the selection of certain foods and macronutrient preference. Sucrase‐isomaltase is a brush border enzyme encoded by the SI gene and plays an important role in starch digestion. Research on genetic variation in SI has mostly focused on rare mutations that result in congenital sucrase‐isomaltase deficiency, a severe digestive disorder. The objective of this study was to determine whether common variants in the SI gene are associated with habitual dietary intake. Methods Fasting blood samples were drawn from a total of 1,400 ethno‐culturally diverse participants aged 20–29 years from the Toronto Nutrigenomics and Health Study for genotyping of 5 single nucleotide polymorphisms (SNPs) in the SI gene: rs4557160 (C > T), rs7649108 (C >T), rs9756306 (G >A), rs12496714 (A >T) and rs13069478 (C >T). Dietary intake was assessed using a one‐month, 196‐item Toronto‐modified Willett food frequency questionnaire. The prevalence of the SI gene variants was compared using χ 2 . An analysis of covariance adjusted for age, sex, ethnicity, BMI, and physical activity was used to determine the association between SI genotypes and dietary intake. Results Among Caucasians rs9756306 and rs12496714 were associated with total energy intake. Carriers of the minor allele had significantly higher energy intakes 2112 vs. 1194 kcal/day, p = 0.02 and 2011 vs. 1990 kcal/day, p = 0.03 respectively). The rs7649108 SNP was associated with starch consumption, whereby carriers of the minor allele had a significantly lower starch intake (115.8 vs. 120.9 g starch/day, p = 0.02). No associations were observed between rs4557160, rs13069479 and dietary intake. Conclusion Polymorphisms in the SI gene are associated with dietary intake patterns. Identifying the genetic determinants of dietary intake and food preference may enhance our understanding of excessive caloric intake and obesity, a common risk factor of many chronic conditions. Support or Funding Information Research support from Mitacs, Prof. Ahmed El‐Sohemy
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".