RESUMO
Purpose: Elevated serum gamma-glutamyltranspeptidase (GGT) is an independent marker of the activation of systemic inflammation, while conditions associated with elevated triglyceride (TG) levels, such as type 2 diabetes, non-alcoholic fatty liver disease, obesity, and metabolic syndrome, are associated with an increased inflammatory burden. Moreover, serum liver enzymes (GGT, alanine aminotransferase [ALT], aspartate aminotransferase [AST], and alkaline phosphatase [ALP]) are associated with metabolic syndrome and its components, including hypertriglyceridemia. However, the relationship between liver enzymes and postprandial hypertriglyceridemia (PHTG) remains unclear. Therefore, in this study we conducted oral fat tolerance tests (OFTTs) to understand the differences in serum liver enzyme levels among individuals with different lipid tolerance levels and their correlation with PHTG. Patients and Methods: For the OFTT, we enrolled 202 non-diabetic volunteers whose fasting triglyceride (TG) levels were less than 1.7 mmol/L in this case-control study. The participants were categorized into two groups according to the TG levels at the 0- and 4-h OFTT: a postprandial normal TG (PNTG) group and a PHTG group. Routine fasting serum biochemical indices, liver enzyme (GGT, ALT, AST, and ALP) levels, and 0- and 4-h OFTT lipid levels were assessed. Results: The PHTG group had significantly higher serum GGT and ALT levels and a lower AST/ALT ratio than those in the PNTG group. However, no significant difference was observed in AST and ALP levels compared with the PNTG group. After adjusting for major confounders, logistic regression analysis indicated a significant correlation between serum GGT and PHTG (odds ratio = 1.168, P < 0.001), but not with ALT level, AST level, AST/ALT ratio, and ALP level. The receiver operating characteristic curve analysis demonstrated that the serum GGT level was an effective predictor of PHTG. Conclusion: Serum GGT levels are significantly associated with PHTG risk and serve as an effective biomarker for early identification.
RESUMO
Roots are involved in acquisition of water and nutrients, as well as in providing structural support to plant. The root system provides a dynamic model for developmental analysis. Here, we investigated quantitative trait loci (QTL), dynamic conditional QTL and epistatic interactions for seedling root traits using an upland cotton F2 population and a constructed genetic map. Totally, 37 QTLs for root traits, 35 dynamic conditional QTLs based on the net increased amount of root traits (root tips, forks, length, surface area and volume) (i) after transplanting 10 days compared to 5 days, and (ii) after transplanting 15 days to 10 days were detected. Obvious dynamic characteristic of QTL and dynamic conditional QTL existed at different developmental stages of root because QTL and dynamic conditional QTL had not been detected simultaneously. We further confirmed that additive and dominance effects of QTL qRSA-chr1-1 in interval time 5 to 10 DAT (days after transplant) offset the effects in 10 to 15 DAT. Lots of two-locus interactions for root traits were identified unconditionally or dynamically, and a few epistatic interactions were only detected simultaneously in interval time of 5-10 DAT and 10-15 DAT, suggesting different interactive genetic mechanisms on root development at different stages. Dynamic conditional QTL and epistasis effects provide new attempts to understand the dynamics of roots and provide clues for root architecture selection in upland cotton.
