Lipogenesis

We analysed the distribution of individual plasma phospholipid fatty acids and expressed them as mol%. We estimated country-specific hazard ratios (HRs) and 95% CIs for associations per one standard deviation (SD, calculated in the overall subcohort) of each SFA with incident type 2 diabetes using Prentice-weighted Cox regression,²² (link) which allows for over-representation of cases in a case-cohort design, and pooled our findings using random-effects meta-analysis. Heterogeneity between countries was expressed as I² values, and we used meta-regression to assess whether the heterogeneity was explained by age, BMI, or sex. We adjusted for potential confounders as follows: model 1 included age (as the underlying timescale), study centre, sex, physical activity index, smoking status, and education level. Model 2 included these parameters plus total energy intake, alcohol intake, and BMI. After recording patterns of association for the nine individual SFAs, we made a post-hoc decision to create three additional exposures based on groupings of SFAs that fit with potential biological action: group 1 (sum of the even-chain SFAs 14:0, 16:0, and 18:0) since these represent both de-novo lipogenesis and dietary intake;9 (link), 11 (link), 14 (link) group 2 (sum of the odd-chain SFAs 15:0 and 17:0) as potential sources of dairy fat;7 (link), 8 (link) and group 3 (sum of the long- or very-long-chain SFAs 20:0, 22:0, 23:0, and 24:0) since these are under-researched SFAs that might undergo distinct peroxisomal fatty acid metabolism rather than mitochondrial metabolism.²⁵ (link) In an additional analysis, we re-grouped 23:0 into group 2 because is it also an odd-chain SFA, and removed it from group 3. Since stearoyl-CoA desaturase-1 catalyses the desaturation of 16:0 to 16:1(n-7) and of 18:0 to 18:1(n-9) through the de-novo lipogenesis pathway, we also estimated stearoyl-CoA desaturase-1 activity using product-to-precursor ratios (ratio of 16:1[n-7] to 16:0 and of 18:1[n-9] to 18:0)6 (link), 15 (link), 26 (link) and assessed each ratio for its association with incident type 2 diabetes.
In a sensitivity analysis based on model 2, we analysed the effects of adjustment for dietary variables (intakes of meat, fruit and vegetables, soft drinks, total dairy products, and carbohydrates [g/day]). We also did an analysis that further accounted for baseline HbA1_C value as a covariate. To minimise the possibility of reverse causality, we also excluded 2348 people with HbA1_C of 6·5% or higher at baseline or those confirmed as cases of type 2 diabetes (n=1048) within the first 2 years after baseline. Further sensitivity analyses on model 2 included adjustment for: additional potential confounders (dietary carbohydrates intake [g/day] and waist circumference [cm]); comorbidity (prevalent myocardial infarction, stroke, or cancer); and the exclusion of 723 people who were probably dietary misreporters (those with a ratio of energy intake to energy requirement in the bottom or top 1% of the distribution). We also studied the association of SFA quintiles with type 2 diabetes incidence in models 1 and 2.
We postulated that circulating SFAs would be derived from diet and through de-novo lipogenesis, and associated with carbohydrate and alcohol consumption.9 (link), 11 (link), 12 (link) Within the subcohort, we studied associations between each circulating SFA and food intakes, using Pearson correlation coefficients and 95% CI adjusted for age, sex, BMI, and energy intake. We used Stata, version 13.1 for all analyses.

POPC lipids dissolved in chloroform were added to a glass vial containing chloroform to obtain 250 µL of a 6 mM solution. Fluorescent GUV membranes were obtained by adding 0.5 µL of a 1 mg/mL solution of Atto 647N-DOPE lipids in chloroform (~0.03 mol%). The chloroform was evaporated under nitrogen flow (10 min) and the lipids were dried under reduced pressure for 1 h to remove residual traces of chloroform. A lipid-mineral oil solution (400 µM lipids) was prepared by adding 3 mL of mineral oil to the dried lipids followed by sonication for 1 h at elevated temperature (40–60 °C). 750 µL of lipid-mineral oil solution was layered on top of 2 mL of outer phase solution in a 5 mL Eppendorf tube. Incubation for 15 min at RT allows lipid monolayer formation at the water-oil interface. Meanwhile, 750 µL of lipid-mineral oil solution and 15 µL of inner phase solution were combined in a 1.5 mL microcentrifuge tube. A water-in-oil emulsion was generated by rubbing the tube over a microtube rack. The water-in-oil emulsion was immediately and carefully pipetted to the biphasic mixture in the 5 mL Eppendorf tube. To generate lipid GUVs, gradual centrifugation (10 min at 300 g followed by 2.5 min at 1500 g) was performed to sediment the denser inverse micelles (surrounded by a lipid monolayer) through the interfacial lipid monolayer. Vesicle pellets at the tube bottom were visible by eye and could thus be easily taken up with a pipette. A 384-glass bottom microtiter plate was first passivated with 50 µL of a Pluronic F-127 solution (10 mg/mL) and then washed once with 50 µL of outer phase solution. Next, the pellet and outer phase solution (~ 50 µL) were transferred to the plate. Another GUV population was added and mixing of both populations was achieved by gently pipetting up and down (10 times). Before freeze-thawing, the plate was centrifuged for 5 min at 1500 g for GUV accumulation and high GUV densities. GUV density is inversely proportional to content loss, since GUVs that are not tightly packed together will lose most of their content to the outer phase. High GUV densities are thus required to minimise content loss and thus improve the overall dynamics of the system in question. If no measures of GUV accumulation are undertaken, content loss can increase up to 80%. All steps, including mineral oil were performed in a custom-made glove box under reduced humidity (<10% relative humidity) except for the centrifugation step for GUV formation.