ESPE2016 Rapid Free Communications Management of Obesity (8 abstracts)
Background: Several studies have correlated Assisted Reproduction Technologies (ART) including classic IVF and Intacytoplasmic Sperm Injection (ICSI) with epigenetic alterations in the offspring that could have long lasting unfavorable metabolic effects. Proteomics, a state-of-the-art technology used for the identification of early biomarkers of disease, has already been implemented in the search of success in ART but not yet for such markers evaluation in offspring of ART.
Objective and hypothesis: To investigate the metabolic status of children born after ICSI with the use of proteomics.
Methods: Demographic, auxological, biochemical and hormonal parameters of 42 ICSI-conceived children and 42 age-matched controls were assessed (mean age: 6.8±2.1 years). Amongst them, 10 couples of children (five females and five males) further matched for birthweight (SGA/AGA/LGA) and parity (twins/singles) were selected for comparative plasma proteomic analysis.
Results: The ICSI group was characterized by a younger gestational age, increased percentage of caesarean sections, smaller birthweight and birth length and advanced maternal age. No differences were observed regarding auxological and initial laboratory data, apart from decreased systolic blood pressure and increased T3 in the ICSI group. The proteomic analysis identified 22 differentially expressed proteins (19 overexpressed and 3 downregulated) in the ICSI group. The majority of the overexpressed proteins are implicated in the acute phase reaction, blood coagulation, complement activation and iron and lipid metabolism, suggesting an unfavorable cardiometabolic profile of these children, at a subclinical level.
Conclusions: This is the first study to use proteomic analysis to assess the metabolic status of children born after ICSI. The results of this study support the importance of close, long-term follow-up of these children especially regarding cardiometabolic risk factors, and highlight the role of proteomics in the early identification of markers of metabolic disturbance.
10 Sep 2016 - 12 Sep 2016