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    • Compared to SFAs convincing evidence observed in our study w

    2018-10-30

    Compared to SFAs, convincing evidence observed in our study was that UFAs are more closely associated with metabolic status in obese individuals. The fluctuations of circulating FFAs in obese phenotypes may be due to the different FA mobilization mechanisms from adipose tissue to blood, where SFAs were found much less mobilized than PUFAs (Connor et al., 1996). Our findings particularly highlight a panel of UFAs that was consistently associated with metabolic status in obese individuals across four independent studies. Two UFAs, PA and DGLA may be potential inflammation markers in predicting the risk of developing MS and monitoring the metabolic status among overweight/obese individuals. PA has been proposed as a lipid-controlling hormone (lipokine) used by adipose tissue to communicate with distant organs and regulate systemic metabolic homeostasis (Cao et al., 2008). Increased levels of plasma PA indicate an increase in stearoyl-CoA desaturase (SCD1) activity (increased DNL) in the liver as it is virtually absent in the diet and thus can be used as a marker for upregulation of this usually inhibited hepatic lipid metabolic pathway (Supplementary Figure S2B) (Gong et al., 2011). Increased DNL means increased formation of diacylglycerol (DAG), which, in turn, contributes to inflammation via release of arachidonic buy OF-1 (AA) from the plasma membrane. DGLA is a key player in the synthetic pathway for pro-inflammatory series 2 prostaglandins and leukotrienes and elevated levels of this PUFA may contribute to the inflammatory phenotype in obesity/MS (Supplementary Figure S2C–D). Recently, it has been proposed that the distinction between HO and UO groups is related to the degree of chronic inflammation present (Perreault et al., 2014; Steffen et al., 2012). This has led to several studies comparing inflammation markers such as levels of TNF-α, adiponectin, leptin, resistin, C-reactive protein, plasminogen activator inhibitor-1 and complement component c3, between HO and UO populations (Steffen et al., 2012; Phillips and Perry, 2013). The major conclusion derived from these studies was that no significant differences were seen for inflammation markers between HO and NW subjects but inflammation markers were found to be elevated in the UO groups. A previous study on 2848 adults found that obese individuals had significantly higher levels of n−6 PUFAs (e.g. DGLA, GLA, and AA) compared to normal and overweight subjects, and DGLA showed strong associations with inflammatory and endothelial activation markers in obesity, e.g. IL-6 and sICAM-1 (Steffen et al., 2012). It was also reported that a high proportion of DGLA in serum cholesterol ester was associated with high concentrations of C-reactive protein, which is a sensitive marker of low-grade inflammation and associated with insulin resistance and T2D (Kurotani et al., 2012). To examine the effects of gender, age and BMI factors on FFA metabolism, we performed subgroup analysis on all of the participants in the cross-sectional study. First, we found three FFAs, i.e., C12:0, C18:1 t9 and C22:6 n3, were significantly increased in females (n=85) compared to males (n=47) in the NW group (Supplementary Figure S3A–C). Second, ten SFAs were consistently increased with age in females only (Supplementary Figure S4). Third, in terms of the BMI factor, we analyzed male subjects only who were able to keep relatively stable FFA levels over time, and found that three FFAs, i.e., C18:0, C14:1 n5 and C22:6 n3 were significantly different between normal weight (n=47) and overweight/obesity (n=39) (Supplementary Figure S3D–F). Thus, we further confirmed that these confounding factors do not affect our findings of UFAs in evaluating and predicting the metabolic status in obesity. Key strengths of the present study are its comprehensive design to study the associations of circulating FFA levels with metabolic phenotypes among several groups of obese participants. In addition, with a complete panel of key metabolic markers measured for all the participants, we were able to compare the FFA profiles with the metabolic status of the study participants. The limitation of the present study is the medium-sized sample sets in the longitudinal study, due to the strict inclusion criteria that all the participants should have complete clinical records and BMI ≥25 at baseline when they were healthy and at a 10-year follow-up time. Future studies examining inflammatory marker association with the FFA profiles discussed in this manuscript are being pursued.