Lipids in Health and Disease最新文献

Background and objectives: The insulin-like growth factor (IGF) axis is postulated to influence early-life adipocyte activity and lipolysis. We investigated whether IGF-1 and IGF-binding proteins (IGFBP-2, IGFBP-3) are associated with the lipids of healthy toddlers.

Methods: Data were collected during the Toddler Milk Intervention trial to test the effect of milk protein on growth in the second year of life in Germany and Spain. Any blood values for IGF-1, IGFBP-2, IGFBP-3, low- and high-density lipoprotein cholesterol (LDL-C, HDL-C), total cholesterol (TC) and triglycerides (TG) were available at 12 and 24 months from 881 to 775 toddlers, respectively. These blood parameters were available from 444 children at both time points. Mixed intercept linear models adjusted for sex, fasting duration, country, and body mass index (BMI) were used to assess the associations between the IGF axis and lipids.

Results: BMI was 17.0 ± 1.4 kg/m² (M ± SD) at 12 months. IGF-1, IGFBP-3 and IGFBP-2 levels were 75.9 ± 36.1 ng/ml, 2630.3 ± 638.4 ng/ml and 575.5 ± 245.6 ng/ml, respectively; the mean LDL-C, HDL-C, TC and TG levels were 80.5 ± 22.9 mg/dl, 42.2 ± 10.9 mg/dl, 141.7 ± 25.5 mg/dl and 101.2 ± 58.9 mg/dl, respectively. While the IGFBP-2 and TG levels were higher at 12 months (p < 0.001) compared to 24 months, all other parameters were lower (p < 0.05). IGF-1 and IGFBP-3 were weakly positively associated with LDL-C, HDL-C and TC, whereas IGFBP-2 was weakly negatively associated with LDL-C, HDL-C and TC.

Conclusion: The IGF axis is weakly associated with circulating lipids. IGF-1 and its binding proteins seem to have a limited impact on lipid profiles of toddlers.

Trial registration: Clinical trial registration number: NCT02907502, 26.04.2016.

Background: Cardiometabolic multimorbidity (CMM) poses a significant global health challenge. The atherogenic index of plasma (AIP) is a promising biomarker for cardiometabolic risk, but there is limited information on its cumulative effect on CMM and the underlying mechanisms. This study investigated the association of cumulative AIP exposure with CMM risk, and explored the mediating roles of the triglyceride glucose (TyG) index and body mass index (BMI).

Methods: This study was based on data from 5,454 participants from the China Health and Retirement Longitudinal Study (CHARLS, 2011 baseline). The participants were stratified into tertiles of cumulative AIP (cuAIP) and classified into three distinct AIP trajectory groups using k-means clustering. Associations between cuAIP levels, AIP trajectories, and CMM incidence were assessed using logistic. The relationship between cuAIP and CMM was further examined using receiver operating characteristic (ROC) curve analysis and restricted cubic splines (RCS). Structural equation modeling was used to evaluate the mediating roles of the TyG index and BMI. Finally, subgroup and sensitivity analyses were conducted to validate the results.

Results: A total of 385 CMM cases were observed during the 7-year follow-up. Cluster analysis revealed the highest CMM incidence (12.1%) in the persistently high AIP trajectory group. Logistic regression models indicated that the highest cuAIP group (OR 2.81, 95% CI: 1.95-4.14) and high AIP trajectory group (OR 2.34, 95% CI: 1.68-3.28) had the highest CMM risk, with consistent results in sensitivity analyses and most subgroups. The AUC of cuAIP for predicting CMM was 0.648, and RCS curves demonstrated increasing CMM incidence with rising cuAIP levels. Mediation analysis indicated that the TyG index and BMI mediated 74% and 26% of the total effect, respectively.

Conclusion: This study establishes AIP as an independent predictor of CMM, whereby its effect is primarily mediated by the TyG index and BMI. These findings support the implementation of integrated clinical strategies to effectively prevent CMM and its associated diseases.