Increased release of arachidonic acid and eicosanoids in iron-overloaded cardiomyocytes.

BACKGROUND: Patients with transfusional iron overload may develop a life-limiting cardiomyopathy. The sensitivity of lipid-metabolizing enzymes to peroxidative injury, as well as the reported effects of arachidonic acid (AA) and metabolites on cardiac rhythm, led us to hypothesize that iron-overloaded cardiomyocytes display alterations in the release of AA and prostaglandins. METHODS AND RESULTS: Neonatal rat ventricular myocytes (NRVMs) cultured for 72 hours in the presence of 80 microgram/mL ferric ammonium citrate displayed an increased rate of AA release, both under resting conditions and after stimulation with agonists such as [Sar(1)]Ang II. Although iron treatment did not affect overall incorporation of [(3)H]AA into NRVM phospholipids, it caused a 2-fold increase in the distribution of precursor in phosphatidylcholine species, with a proportional decrease in phosphatidylinositol, phosphatidylserine, and phosphatidylethanolamine. Increased release of AA in iron-overloaded NRVMs was reduced by the diacylglycerol lipase inhibitor RHC80267 but was largely insensitive to inhibitors of phospholipases A(2) and C. Iron-overloaded cardiomyocytes also displayed increased production of eicosanoids and induction of cyclooxygenase-2 after stimulation with interleukin-1alpha. CONCLUSIONS: Iron overload enhances AA release and incorporation of AA into phosphatidylcholine, as well as cyclooxygenase-2 induction and eicosanoid production, in NRVMS: The effects of AA and metabolites on cardiomyocyte rhythmicity suggest a causal connection between these signals and electromechanical alterations in iron-overload-induced cardiomyopathy.

Electrocardiographic prediction of abnormal genotype in congenital long QT syndrome: experience in 101 related family members.

INTRODUCTION: Previous studies showed that diagnosing congenital long QT syndrome (LQTS) is difficult due to variable penetrance and genetic heterogeneity, especially when subjects from multiple families with diverse mutations are combined. We hypothesized that a combination of clinical and ECG techniques could identify gene carriers within a single family with congenital LQTS. METHODS AND RESULTS: One hundred one genotyped members of a family with LQTS, including 26 carriers of a HERG mutation, underwent history and ECG analysis. Forty-eight family members also underwent exercise testing with QT and T wave alternans (TWA) analysis and 24-hour Holter monitoring with QT and heart rate variability analysis. A logistic regression model, which included age, gender, QTc, and QTc by age, provided the best prediction of gene carrier status, although there was substantial overlap (78%) of QTc among subjects with and without the mutation. QTc was not helpful as a discriminator in children < or = 13 years. TWA (observed infrequently) did not add significantly to the model's ability to predict abnormal genotype. CONCLUSION: Even in this homogeneous LQTS population, the phenotype was so variable that clinical and detailed ECG analyses did not permit an accurate diagnosis of gene carrier status, especially in children. Sustained microvolt TWA was a specific (100%) but insensitive (18%) marker for LQTS. Its ability to predict risk of arrhythmia in this population remains to be determined. Genetic testing serves an essential role in screening for carriers of LQTS.