Widely targeted plasma lipidomic analysis of Term Low Birth Weight Infants: unraveling signatures and implications for early growth patterns

Low birth weight is recognized as a risk factor for adult metabolic and cardiovascular diseases. This study investigates whether term low birth weight (TLBW) neonates, who have been exposed to unfavorable settings, demonstrate compromised lipid metabolism. A widely targeted lipidomic analysis was conducted using ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) on 59 plasma samples (28 TLBW and 31 term normal birth weight (TNBW) neonates. We conducted univariate and multivariate analyses to identify differential lipids. Spearman's correlation coefficient assessed the association between lipid content at birth and Z-scores for the subsequent physical growth of enrolled children. A total of 1523 lipids in 36 subcategories across 6 major categories were detected. 269 differential lipids were discerned, with 114 up-regulated and 155 down-regulated. In the TLBW group, we observed higher levels of sphingomyelins (including SM(d18:1/16:1), SM(d18:2/23:1), SM(d18:1/22:0), and SM(d18:2/24:1)), Hex3Cer(d18:1/16:0), as well as phosphatidylcholines (PC(O-14:0_20:4) and PC(O-16:0_20:4)), and cholesterol esters (CE (20:4)). In contrast, phosphatidylethanolamines (PE) such as PE (18:2_22:1), PE (18:1_22:1), and triglyceride (TG(10:0_16:2_18:2)) were lower. The KEGG enrichment analysis revealed a consistent alteration in both sphingolipid metabolism and steroid biosynthesis. Moreover, PC(O-16:0_20:4), Hex3Cer(d18:1/16:0), and CE(20:4) exhibited positive correlations with the Z-score of height-for-age at follow-up, while PE(O-18:1_24:4) and PS(20:2_22:4) showed negative correlations with the Z-score of weight-for-age. Our findings reveal novel lipidomic differences between TLBW and TNBW neonates. The observed lipid variations at birth, including sphingomyelins and glycerophospholipids, could affect subsequent growth. Further studies are needed to validate these findings in diverse populations, address confounding factors, and investigate underlying mechanisms.