Association between fatty acid biomarkers of dairy fat consumption and insulin sensitivity in humans
Bibliographic record
Abstract
Background: Epidemiological studies have shown that greater consumption of dairy fat is associated with lower risk of type 2 diabetes (T2D).This inverse association is particularly strong when C15:0, C17:0, and tC16:1n-7 fatty acid (FA) proportions in circulation are used as biomarkers of dairy fat intake.Evidence for an association between plasma and serum levels of these biomarkers and insulin resistance, as measured by surrogate indices, remains inconclusive.Only two studies have assessed this relationship with biomarkers in adipose tissue which reflect long-term intake of FA.Branched-chain FA are emerging as potential markers of dairy fat intake and may help clarify the association between dairy intake and T2D.Objective: To evaluate the association between established and potential biomarkers of dairy fat intake in adipose tissue and hyperinsulinemic clamp-based measures of insulin sensitivity.Methods: Subcutaneous adipose tissue of 58 adults (mean age 47 y, 57% females, 45% with T2D) were analyzed.Fatty acids (n=57), including odd-chained FA, branched-chain FA and conjugated linoleic acids (CLA), were quantified using gas chromatography-mass spectrometry.Insulin sensitivity, expressed as insulin sensitivity index, glucose rate of appearance and rate of disposal, was assessed using the hyperinsulinemic-euglycemic clamp.Dietary intake was estimated from 3-day food diaries and a 24-h recall.Linear regression models examined the association between FA biomarkers of dairy fat intake and insulin sensitivity.Results: A total of 57 FA were detected across all samples, with 37 present in 90% of samples and 19% being the targeted FA.The clamp-based insulin sensitivity index was found to range from 0.07 to 2.22 (mg/kg LBM•min)/(pmol/L).In a multivariable analysis adjusted for age, sex, BMI, and T2D status, FA C15:0 (𝛽=4.01[1.37, 6.64], p=0.004), anteiso-C15:0 (𝛽= 2.51 [0.707, 4.31], p=0.007) and cis-9 trans-11 CLA (𝛽= 5.30 [1.04, 9.57], p=0.02) in subcutaneous adipose tissue were positively and independently associated with peripheral insulin sensitivity.There was inverse association between C17:0 ( 𝛽=-0.014[-0.699, 0.671], p=0.97), and tC16:1n-7(𝛽=-0.034[-0.239,0.171],p=0.74), and whole-body insulin sensitivity.The method for FA detection was optimized with sufficient resolution and sensitivity for target FA.However, difficulties in the analysis included distinguishing between endogenous and exogenous internal standards, co-elution of antioxidant with FA, the presence of contaminants and unidentifiable FA, and signal saturation for abundant FA.Conclusion: Increased proportions of FA in adipose tissue considered as established and emerging biomarkers of dairy fat intake were positively associated with insulin sensitivity, independently of known factors.The findings imply that the consistent inverse association between dairy fat intake and T2D outcomes may be attributed to improved insulin sensitivity.Further optimization of the FA measurement method and additional studies are required to validate these findings.CE -Cholesterol ester CFG -Canada's Food Guide CLA -Conjugated linoleic acid CVD -Cardiovascular disease DR -Dietary recall DXA -Dual-energy X-ray absorptiometry FA -Fatty acids FAME -Fatty acid methyl ester FFA -Free fatty acids FFQ -Food frequency questionnaire FID -Flame ionization detection HbA1C -Glycated hemoglobin HEC -Hyperinsulinemic-euglycemic clamp HOMA-IR -Homeostatic model of assessment insulin resistance IS -Insulin sensitivity ISI -Insulin sensitivity index GC-Gas chromatography LBM -Lean body mass MS -Mass spectrometry OCFA -Odd chained fatty acid OGTT -Oral glucose tolerance test PL -Phospholipid Ra -Rate of glucose appearance Rd -Rate of glucose disposal SAT -Subcutaneous adipose tissue SFA -Saturated fatty acids TAG -Triacylglycerides T2D -Type 2 diabetes
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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 | 0.000 | 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) | 0.004 | 0.001 |
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".