Integrative Analysis of Lipid Profiles in Plasma Allows Cardiometabolic Risk Factor Clustering in Children with Metabolically Unhealthy Obesity

Abstract

Hypertension, central obesity, hyperglycemia, and dyslipidemia are key risk factors for cardiovascular disease. However, the specific factors contributing to the development of unfavorable cardiometabolic characteristics in children with obesity are unknown. In this study, we investigated the cross-sectional relationships between cytokines, irisin, and fatty acid (FA) composition in plasma in school-age children with metabolically healthy and unhealthy obesity (MHO and MUO, respectively) of the same age and body mass index and waist circumference percentiles. We compared the data with that of children with normal weight (NW). We found that inflammatory cytokines and low irisin plasma concentrations are associated with obesity but not with cardiometabolic risk (CMR). Lipid profiles showed that children with MUO have a distinctive FA profile compared with children with MHO and NW, whereas children with MHO shared 88% of the FA profile with the NW group. Among all FAs, concentration of myristic acid (14 : 0), arachidic acid (20 : 0), and n-3 polyunsaturated FAs (PUFAs) was higher in children with MHO, whereas n-6 PUFAs such as arachidonic acid (20 : 4n6) had a significant contribution in defining MUO. These data suggest that the plasma FA profile is not only a central link to obesity but also may act as an indicator of CMR presence.

Untargeted Metabolomics Analysis of the Serum Metabolic Signature of Childhood Obesity

“…We showed that lipids are the most crucial group of altered metabolites in obese children compared to the non-obese control group. This observation aligns with the other metabolomics studies on obesity in adults [ 38 , 39 ] and limited data on pediatric populations [ 40 , 41 ]. Obesity is associated with elevated levels of TGs [ 42 , 43 ], sphingolipids [ 44 ], SM [ 45 ], CE [ 43 ], and phospholipids (PLs) [ 46 ] in adult obese patients.…”

Physicochemical Properties and Sensory Acceptability of a Next-Generation Functional Chocolate Added with Omega-3 Polyunsaturated Fatty Acids and Probiotics

“…Separation of FAMEs was performed in a fused-silica SP-2380 capillary column (100 m × 0.25 mm i.d., 0.2 µm film thickness; Supelco, Bellefonte, PA, USA). Chromatographic parameters, and FAMEs identification and quantification were performed according to Castillo et al [ 19 ]. Quantification for each compound, and the total amount of fatty acids were calculated by the AOAC method 996.06 [ 20 ].…”

The Enigmatic Aliphatic Acetogenins and Their Correlations With Lipids During Seed Germination and Leaf Development of Avocado (Persea americana Mill.)

“…Avocado subsamples (from study I or II ), AcO-avocadene, which is an NMR-characterized free acetogenin analytical standard ( Rodríguez-Sánchez et al, 2013 ), and Avosafe ® were independently derivatized ( Castillo et al, 2020 ). Undecanoic acid (200 ppm, Nu Chek Prep Inc., MA, United States) was used as an internal quantification standard.…”

“…A standard mixture containing 39 FAMEs (GLC 566, Nu Chek Prep Inc., MA, United States) or standardized AcOMEs obtained in the previous section ( Study II ) were analyzed by GC–MS chromatography (Agilent 7890B/5977A, Agilent Technologies Inc., CA, United States) to identify the lipids. A previously developed method was used ( Castillo et al, 2020 ). Having as reference fragmentation patterns of FAMEs ( Jabbar et al, 2014 ; Busta et al, 2016 ) and Mclafferty rearrangement characteristic of esters ( McLafferty, 1956 ; Weiler, 1972 ), the expected fragmentation patterns of each of the free AcO-acetogenins reported here (based on their structure) were matched to their observed mass spectra ( Supplementary Figure 2 ).…”

“…Fatty acid methyl ethers and AcOMEs profiles present in oil extracts from avocado (from study I or II ) were determined by gas chromatography using a flame ionization detector (GC- FID 6850A, Agilent Technologies Inc., CA, United States). The column and chromatographic conditions were those used for GC-MS ( Castillo et al, 2020 ). Quantification by GC-FID was determined by comparing response factors of analytical standards, according to the AOAC method 996.06 ( AOAC, 2000 ).…”