Impact of age on cardiometabolic health in children at adiposity rebound: the role of genetic mechanisms.

BACKGROUND

Identifying effective predictors early in life is crucial to enable timely prevention and intervention to improve cardiometabolic health outcomes. Adiposity rebound (AR) is an important period in early life, with earlier AR increasing the risk of cardiometabolic abnormalities. However, the role and mechanism of genetic factors in this association are unclear. Therefore, this study reviews the potential genetic mechanisms influencing the age at AR, as well as the genetic mechanisms linking earlier AR with cardiometabolic abnormalities.

DATA SOURCES

A comprehensive literature search was conducted in PubMed and China National Knowledge Infrastructure databases using a combination of medical subject headings terms and related keywords, including "adiposity rebound", "cardiometabolic", "obesity", "BMI trajectory", "diabetes mellitus", "dyslipidemias", "hypertension", "metabolic syndrome", "genetics", and "epigenetic". Citation tracking was performed as a supplementary search strategy. All potentially relevant articles were subsequently subjected to full-text evaluation for eligibility assessment.

RESULTS

Polymorphisms in the DMRT1, FTO, LEPR, and TFAP2B genes, along with obesity susceptibility, can influence the age at AR. Single-nucleotide polymorphisms associated with the age at AR are enriched in the insulin-like growth factor 1 (IGF-1) signaling pathway, which can be modulated by the LEPR and TFAP2B genes. Shared genetic mechanisms between cardiometabolic abnormalities and the age at AR are influenced by obesity-related genetic variants. These variants regulate the growth hormone (GH)/IGF-1 axis, advancing AR and leading to cardiometabolic abnormalities. Earlier AR alters adiponectin and leptin levels, further activating the GH/IGF-1 axis and creating a vicious cycle. Long-term breastfeeding can counteract the adverse effects of obesity-related genetic susceptibility on AR timing, thereby reducing the genetic risk of cardiometabolic abnormalities.

CONCLUSIONS

Our results support earlier AR as a marker for identifying cardiometabolic risk and screening high-risk populations at the genetic level.