Plasma metabolites and lipids predict insulin sensitivity improvement in obese, nondiabetic individuals after a 2-phase dietary intervention.
Study Goal
The researchers aimed to predict insulin sensitivity improvements after a low-calorie-diet intervention using baseline variables, including phosphatidylcholine 0-34:1.
Results Summary
The study found that phosphatidylcholine 0-34:1, along with baseline Matsuda index and proline, was a key predictor of insulin sensitivity improvements after a low-calorie-diet intervention, with the model achieving an AUC of 0.75 in validation.
Population
Overweight or obese nondiabetic subjects (n=433) from the DiOGenes Study.
Effective Dosage
Not specified
Duration
8-week low-calorie-diet intervention, with outcomes measured at 6 months post-intervention.
Interactions
None mentioned
| Intervention | Direction | Endpoint | Population | Dosage | Impact | Claim # |
|---|---|---|---|---|---|---|
low-calorie-diet (LCD) intervention (800 kcal/d) | decrease | type 2 diabetes | obese individuals | - | aims to reduce the risk | #1 |
low-calorie-diet (LCD) intervention (800 kcal/d) | increase | glycemic control | obese individuals | - | improving | #2 |
low-calorie-diet (LCD) intervention (800 kcal/d) | increase | insulin sensitivity | individuals | - | show improvements | #3 |
initial modeling with baseline clinical variables | no change | area under the curve (AUC) | testing dataset | 0.69 | showed limited performance | #4 |
omics model based on 27 variables | increase | area under the curve (AUC) | - | 0.77 | Significantly better performance was achieved | #5 |
simplified model | no change | area under the curve (AUC) | validation set | 0.75 | successfully replicated | #6 |
replacing the Matsuda index with homeostasis model assessment of insulin resistance | decrease | area under the curve (AUC) | - | 0.72 | Marginally lower performance was obtained | #7 |
BACKGROUND: Weight loss in obese individuals aims to reduce the risk of type 2 diabetes by improving glycemic control. Yet, significant intersubject variability is observed and the outcomes remain poorly predictable. OBJECTIVE: The aim of the study was to predict whether an individual will show improvements in insulin sensitivity above or below the median population change at 6 mo after a low-calorie-diet (LCD) intervention. DESIGN: With the use of plasma lipidomics and metabolomics for 433 subjects from the Diet, Obesity, and Genes (DiOGenes) Study, we attempted to predict good or poor Matsuda index improvements 6 mo after an 8-wk LCD intervention (800 kcal/d). Three independent analysis groups were defined: "training" (n = 119) for model construction, "testing" (n = 162) for model comparison, and "validation" (n = 152) to validate the final model. RESULTS: Initial modeling with baseline clinical variables (body mass index, Matsuda index, total lipid concentrations, sex, age) showed limited performance [area under the curve (AUC) on the "testing dataset" = 0.69; 95% CI: 0.61, 0.77]. Significantly better performance was achieved with an omics model based on 27 variables (AUC = 0.77; 95% CI: 0.70, 0.85; P = 0.0297). This model could be greatly simplified while keeping the same performance. The simplified model relied on baseline Matsuda index, proline, and phosphatidylcholine 0-34:1. It successfully replicated on the validation set (AUC = 0.75; 95% CI: 0.67, 0.83) with the following characteristics: specificity = 0.73, sensitivity = 0.68, negative predictive value = 0.60, and positive predictive value = 0.80. Marginally lower performance was obtained when replacing the Matsuda index with homeostasis model assessment of insulin resistance (AUC = 0.72; 95% CI: 0.64, 0.80; P = 0.08). CONCLUSIONS: Our study proposes a model to predict insulin sensitivity improvements, 6 mo after LCD completion in a large population of overweight or obese nondiabetic subjects. It relies on baseline information from 3 variables, accessible from blood samples. This model may help clinicians assessing the large variability in dietary interventions and predict outcomes before an intervention. This trial was registered at www.clinicaltrials.gov as NCT00390637.