30 research outputs found

    Proximal correlates of metabolic phenotypes during ‘at-risk' and ‘case' stages of the metabolic disease continuum

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    Extent: 11p.OBJECTIVE: To examine the social and behavioural correlates of metabolic phenotypes during ‘at-risk’ and ‘case’ stages of the metabolic disease continuum. DESIGN: Cross-sectional study of a random population sample. PARTICIPANTS: A total of 718 community-dwelling adults (57% female), aged 18--92 years from a regional South Australian city. MEASUREMENTS: Total body fat and lean mass and abdominal fat mass were assessed by dual energy x-ray absorptiometry. Fasting venous blood was collected in the morning for assessment of glycated haemoglobin, plasma glucose, serum triglycerides, cholesterol lipoproteins and insulin. Seated blood pressure (BP) was measured. Physical activity and smoking, alcohol and diet (96-item food frequency), sleep duration and frequency of sleep disordered breathing (SDB) symptoms, and family history of cardiometabolic disease, education, lifetime occupation and household income were assessed by questionnaire. Current medications were determined by clinical inventory. RESULTS: 36.5% were pharmacologically managed for a metabolic risk factor or had known diabetes (‘cases’), otherwise were classified as the ‘at-risk’ population. In both ‘at-risk’ and ‘cases’, four major metabolic phenotypes were identified using principal components analysis that explained over 77% of the metabolic variance between people: fat mass/insulinemia (FMI); BP; lipidaemia/lean mass (LLM) and glycaemia (GLY). The BP phenotype was uncorrelated with other phenotypes in ‘cases’, whereas all phenotypes were inter-correlated in the ‘at-risk’. Over and above other socioeconomic and behavioural factors, medications were the dominant correlates of all phenotypes in ‘cases’ and SDB symptom frequency was most strongly associated with FMI, LLM and GLY phenotypes in the ‘at-risk’. CONCLUSION: Previous research has shown FMI, LLM and GLY phenotypes to be most strongly predictive of diabetes development. Reducing SDB symptom frequency and optimising the duration of sleep may be important concomitant interventions to standard diabetes risk reduction interventions. Prospective studies are required to examine this hypothesis.MT Haren, G Misan, JF Grant, JD Buckley, PRC Howe, AW Taylor, J Newbury and RA McDermot

    Proximal correlates of metabolic phenotypes during ‘at-risk' and ‘case' stages of the metabolic disease continuum

    Get PDF
    Extent: 11p.OBJECTIVE: To examine the social and behavioural correlates of metabolic phenotypes during ‘at-risk’ and ‘case’ stages of the metabolic disease continuum. DESIGN: Cross-sectional study of a random population sample. PARTICIPANTS: A total of 718 community-dwelling adults (57% female), aged 18--92 years from a regional South Australian city. MEASUREMENTS: Total body fat and lean mass and abdominal fat mass were assessed by dual energy x-ray absorptiometry. Fasting venous blood was collected in the morning for assessment of glycated haemoglobin, plasma glucose, serum triglycerides, cholesterol lipoproteins and insulin. Seated blood pressure (BP) was measured. Physical activity and smoking, alcohol and diet (96-item food frequency), sleep duration and frequency of sleep disordered breathing (SDB) symptoms, and family history of cardiometabolic disease, education, lifetime occupation and household income were assessed by questionnaire. Current medications were determined by clinical inventory. RESULTS: 36.5% were pharmacologically managed for a metabolic risk factor or had known diabetes (‘cases’), otherwise were classified as the ‘at-risk’ population. In both ‘at-risk’ and ‘cases’, four major metabolic phenotypes were identified using principal components analysis that explained over 77% of the metabolic variance between people: fat mass/insulinemia (FMI); BP; lipidaemia/lean mass (LLM) and glycaemia (GLY). The BP phenotype was uncorrelated with other phenotypes in ‘cases’, whereas all phenotypes were inter-correlated in the ‘at-risk’. Over and above other socioeconomic and behavioural factors, medications were the dominant correlates of all phenotypes in ‘cases’ and SDB symptom frequency was most strongly associated with FMI, LLM and GLY phenotypes in the ‘at-risk’. CONCLUSION: Previous research has shown FMI, LLM and GLY phenotypes to be most strongly predictive of diabetes development. Reducing SDB symptom frequency and optimising the duration of sleep may be important concomitant interventions to standard diabetes risk reduction interventions. Prospective studies are required to examine this hypothesis.MT Haren, G Misan, JF Grant, JD Buckley, PRC Howe, AW Taylor, J Newbury and RA McDermot

    Unique cellular and mitochondrial defects mediate FK506-induced islet β-cell dysfunction

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    OBJECTIVE: Determine biological mechanisms involved in post transplantation diabetes mellitus caused by the immunosuppressant FK506. METHODS: INS-1 cells and isolated rat islets were incubated with vehicle or FK506 and harvested at 24 hr intervals. Cells were assessed for viability, apoptosis, proliferation, cell insulin secretion and content. Gene expression studies by microarray analysis, qPCR and motifADE analysis of the microarray data identified potential FK506-mediated pathways and regulatory motifs. Mitochondrial functions, including cell respiration, mitochondrial content and bioenergetics were assessed. RESULTS: Cell replication, viability, insulin secretion, oxygen consumption, and mitochondrial content were decreased (p < 0.05) 1.2-, 1.27-, 1.77-, 1.32-, and 1.43-fold, respectively after 48 hr FK506 treatment. Differences increased with time. FK506 (50 ng/ml) and Cyclosporine A (800 ng/ml) had comparable effects. FK 506 significantly decreased mitochondrial content and mitochondrial bioenergetics and showed a trend towards decreased oxygen consumption in isolated islets. Cell apoptosis and proliferation, mitochondrial DNA copy number and ATP/ADP ratios were not significantly affected. Pathway analysis of microarray data showed FK506 modification of pathways involving ATP metabolism, membrane trafficking and cytoskeleton remodeling. PGC1-α mRNA was down-regulated by FK506. MotifADE identified nuclear factor of activated T-cells (NFAT), an important mediator of β cell survival and function, as a potential factor mediating both up- and down-regulation of gene expression. CONCLUSIONS: At pharmacologically relevant concentrations FK506 decreases insulin secretion and reduces mitochondrial density and function without changing apoptosis rates, suggesting that post transplantation diabetes induced by FK506 may be mediated by its effects on mitochondrial function
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