Eugene P. Rhee

Hyperphosphatemia, calcitriol deficiency, and secondary hyperparathyroidism (SHPT) are common complications of chronic kidney disease (CKD). Fibroblast growth factor-23 (FGF-23) is a novel phosphaturic hormone that also inhibits renal 1alpha-hydroxylase activity and thus may be involved in the pathogenesis of SHPT. Several hypotheses were tested: that FGF-23 increases as renal function declines; is linearly associated with serum phosphate levels; is associated with increased phosphaturia independent of parathyroid hormone (PTH); and is associated with decreased calcitriol levels independent of renal function, hyperphosphatemia, and vitamin D stores. FGF-23, PTH, 25(OH)D3, calcitriol, calcium, phosphate, and urinary fractional excretion of phosphate (Fe(PO4)) were measured in 80 CKD patients. Multiple linear regression was used to test the hypotheses. FGF-23 and PTH were inversely associated with estimated GFR (eGFR), whereas calcitriol levels were linearly associated with eGFR. Hyperphosphatemia and hypocalcemia were present in only 12 and 6% of patients, respectively, all of whose eGFR was <30. Increased Fe(PO4) was associated with decreased eGFR, and both increased FGF-23 and PTH were independently associated with increased Fe(PO4). Increased FGF-23 and decreased 25(OH)D3 were independent predictors of decreased calcitriol, but the effects on calcitriol levels of renal function itself and hyperphosphatemia were completely extinguished by adjusting for FGF-23. It is concluded that FGF-23 levels increase early in CKD before the development of serum mineral abnormalities and are independently associated with serum phosphate, Fe(PO4), and calcitriol deficiency. Increased FGF-23 may contribute to maintaining normal serum phosphate levels in the face of advancing CKD but may worsen calcitriol deficiency and thus may be a central factor in the early pathogenesis of SHPT.

Dyslipidemia is an independent risk factor for type 2 diabetes, although exactly which of the many plasma lipids contribute to this remains unclear. We therefore investigated whether lipid profiling can inform diabetes prediction by performing liquid chromatography/mass spectrometry-based lipid profiling in 189 individuals who developed type 2 diabetes and 189 matched disease-free individuals, with over 12 years of follow up in the Framingham Heart Study. We found that lipids of lower carbon number and double bond content were associated with an increased risk of diabetes, whereas lipids of higher carbon number and double bond content were associated with decreased risk. This pattern was strongest for triacylglycerols (TAGs) and persisted after multivariable adjustment for age, sex, BMI, fasting glucose, fasting insulin, total triglycerides, and HDL cholesterol. A combination of 2 TAGs further improved diabetes prediction. To explore potential mechanisms that modulate the distribution of plasma lipids, we performed lipid profiling during oral glucose tolerance testing, pharmacologic interventions, and acute exercise testing. Levels of TAGs associated with increased risk for diabetes decreased in response to insulin action and were elevated in the setting of insulin resistance. Conversely, levels of TAGs associated with decreased diabetes risk rose in response to insulin and were poorly correlated with insulin resistance. These studies identify a relationship between lipid acyl chain content and diabetes risk and demonstrate how lipid profiling could aid in clinical risk assessment.

BACKGROUND: Although metabolic risk factors are known to cluster in individuals who are prone to developing diabetes mellitus and cardiovascular disease, the underlying biological mechanisms remain poorly understood. METHODS AND RESULTS: To identify pathways associated with cardiometabolic risk, we used liquid chromatography/mass spectrometry to determine the plasma concentrations of 45 distinct metabolites and to examine their relation to cardiometabolic risk in the Framingham Heart Study (FHS; n=1015) and the Malmö Diet and Cancer Study (MDC; n=746). We then interrogated significant findings in experimental models of cardiovascular and metabolic disease. We observed that metabolic risk factors (obesity, insulin resistance, high blood pressure, and dyslipidemia) were associated with multiple metabolites, including branched-chain amino acids, other hydrophobic amino acids, tryptophan breakdown products, and nucleotide metabolites. We observed strong associations of insulin resistance traits with glutamine (standardized regression coefficients, -0.04 to -0.22 per 1-SD change in log-glutamine; P<0.001), glutamate (0.05 to 0.14; P<0.001), and the glutamine-to-glutamate ratio (-0.05 to -0.20; P<0.001) in the discovery sample (FHS); similar associations were observed in the replication sample (MDC). High glutamine-to-glutamate ratio was associated with lower risk of incident diabetes mellitus in FHS (odds ratio, 0.79; adjusted P=0.03) but not in MDC. In experimental models, administration of glutamine in mice led to both increased glucose tolerance (P=0.01) and decreased blood pressure (P<0.05). CONCLUSIONS: Biochemical profiling identified circulating metabolites not previously associated with metabolic traits. Experimentally interrogating one of these pathways demonstrated that excess glutamine relative to glutamate, resulting from exogenous administration, is associated with reduced metabolic risk in mice.