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Tristetraprolin, Inflammation, and Metabolic Syndrome in Arab Adults: A Case Control Study.

ABSTRACT: Tristetraprolin (TTP) is an mRNA binding protein suggested to have a substantial role in regulating the mRNA expression of numerous inflammatory factors, but data on TTP and its association with metabolic syndrome (MetS), a chronic low-grade inflammatory disorder, are scarce. We hypothesize that TTP may modulate MetS and its components. A total of 200 Saudi adults (aged 38.6 ± 8.3 years) were included in this cross-sectional study. Anthropometrics data were collected and fasting blood glucose taken for the assessment of glycemic, lipids and inflammatory markers using commercially available assays. The National Cholesterol Education Program Adult Treatment Panel (NCEP ATP III) criteria were used to define MetS. Results showed significantly higher levels of TTP in the MetS group than in controls [288.1 pg/mL vs. 150.9 pg/mL, p < 0.001]. Circulating TTP was significantly associated with tumor necrosis factor alpha [TNF-α, R = 0.30, p < 0.05], interleukin 1β [IL-1β, R = 0.41, p < 0.01] and C-reactive protein [CRP, R = 0.36, p < 0.01], adiponectin [R = 0.36, p < 0.05], insulin [R = 0.37, p < 0.05], and insulin resistance [HOMA-IR, R = 0.40, p < 0.05]. Receiver operating characteristics (ROC) suggest a potential use of TTP as diagnostic biomarker for MetS [AUC = 0.819, p < 0.001]. The findings suggest that TTP is associated with inflammation and glycemia, which may influence MetS. TTP is a promising diagnostic biomarker for MetS which can be confirmed in larger cohorts.

SUBMITTER: Al-Daghri NM

PROVIDER: S-EPMC8235193 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:RationaleCross-sectional studies demonstrate an association between metabolic syndrome and impaired lung function.ObjectivesTo define if metabolic syndrome biomarkers are risk factors for loss of lung function after irritant exposure.MethodsA nested case-control study of Fire Department of New York personnel with normal pre-September 11th FEV(1) and who presented for subspecialty pulmonary evaluation before March 10, 2008. We correlated metabolic syndrome biomarkers obtained within 6 months of World Trade Center dust exposure with subsequent FEV(1). FEV(1) at subspecialty pulmonary evaluation within 6.5 years defined disease status; cases had FEV(1) less than lower limit of normal, whereas control subjects had FEV(1) greater than or equal to lower limit of normal.Measurements and main resultsClinical data and serum sampled at the first monitoring examination within 6 months of September 11, 2001, assessed body mass index, heart rate, serum glucose, triglycerides and high-density lipoprotein (HDL), leptin, pancreatic polypeptide, and amylin. Cases and control subjects had significant differences in HDL less than 40 mg/dl with triglycerides greater than or equal to 150 mg/dl, heart rate greater than or equal to 66 bpm, and leptin greater than or equal to 10,300 pg/ml. Each increased the odds of abnormal FEV(1) at pulmonary evaluation by more than twofold, whereas amylin greater than or equal to 116 pg/ml decreased the odds by 84%, in a multibiomarker model adjusting for age, race, body mass index, and World Trade Center arrival time. This model had a sensitivity of 41%, a specificity of 86%, and a receiver operating characteristic area under the curve of 0.77.ConclusionsAbnormal triglycerides and HDL and elevated heart rate and leptin are independent risk factors of greater susceptibility to lung function impairment after September 11, 2001, whereas elevated amylin is protective. Metabolic biomarkers are predictors of lung disease, and may be useful for assessing risk of impaired lung function in response to particulate inhalation.

Project description:BackgroundDefining the metabolic syndrome (MetS) in children remains challenging. Furthermore, a dichotomous MetS diagnosis can limit the power to study associations. We sought to characterize the serum metabolite signature of the MetS in early childhood using high-throughput metabolomic technologies that allow comprehensive profiling of metabolic status from a biospecimen.MethodsIn the Family Atherosclerosis Monitoring In earLY life (FAMILY) prospective birth cohort study, we selected 228 cases of MetS and 228 matched controls among children age 5 years. In addition, a continuous MetS risk score was calculated for all 456 participants. Comprehensive metabolite profiling was performed on fasting serum samples using multisegment injection-capillary electrophoresis-mass spectrometry. Multivariable regression models were applied to test metabolite associations with MetS adjusting for covariates of screen time, diet quality, physical activity, night sleep, socioeconomic status, age, and sex.ResultsCompared to controls, thirteen serum metabolites were identified in MetS cases when using multivariable regression models, and using the quantitative MetS score, an additional eight metabolites were identified. These included metabolites associated with gluconeogenesis (glucose (odds ratio (OR) 1.55 [95% CI 1.25-1.93]) and glutamine/glutamate ratio (OR 0.82 [95% CI 0.67-1.00])) and the alanine-glucose cycle (alanine (OR 1.41 [95% CI 1.16-1.73])), amino acids metabolism (tyrosine (OR 1.33 [95% CI 1.10-1.63]), threonine (OR 1.24 [95% CI 1.02-1.51]), monomethylarginine (OR 1.33 [95% CI 1.09-1.64]) and lysine (OR 1.23 [95% CI 1.01-1.50])), tryptophan metabolism (tryptophan (OR 0.78 [95% CI 0.64-0.95])), and fatty acids metabolism (carnitine (OR 1.24 [95% CI 1.02-1.51])). The quantitative MetS risk score was more powerful than the dichotomous outcome in consistently detecting this metabolite signature.ConclusionsA distinct metabolite signature of pediatric MetS is detectable in children as young as 5 years old and may improve risk assessment at early stages of development.

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Tristetraprolin, Inflammation, and Metabolic Syndrome in Arab Adults: A Case Control Study.

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