Citations

Background and Purpose— Coronary artery disease is the leading cause of death after TIA. Reliable estimates of the risk of MI after TIA, however, are lacking. Methods— Our purpose was to determine the incidence of and risk factors for MI after TIA. We cross-referenced preexisting incidence cohorts from the Rochester Epidemiology Project for TIA (1985–1994) and MI (1979–2006) to identify all community residents with incident MI after incident TIA. Incidence of MI after TIA was determined using Kaplan–Meier life-table methods. This was compared to the age-, sex-, and period-specific MI incidences in the general population. Proportional hazards regression analysis was used to examine associations between clinical variables and the occurrence of MI after TIA. Results— Average annual incidence of MI after TIA was 0.95%. Relative risk for incident MI in the TIA cohort compared to the general population was 2.09 (95% CI, 1.52–2.81). This was highest in patients younger than 60 years old (relative risk, 15.1; 95% CI, 4.11–38.6). Increasing age (hazard ratio, 1.51 per 10 years; 95% CI, 1.14–2.01), male sex (hazard ratio, 2.19; 95% CI, 1.18–4.06), and the use of lipid-lowering therapy at the time of TIA (hazard ratio, 3.10; 95% CI, 1.20–8.00) were independent risk factors for MI after TIA. Conclusions— Average annual incidence of MI after TIA is ≈1%, approximately double that of the general population. The relative risk increase is especially high in patients younger than 60 years old. These data are useful for identifying subgroups of patients with TIA at highest risk for subsequent MI.

Background— Excitation-contraction coupling in striated muscle requires proper communication of plasmalemmal voltage-activated Ca 2+ channels and Ca 2+ release channels on sarcoplasmic reticulum within junctional membrane complexes. Although previous studies revealed a loss of junctional membrane complexes and embryonic lethality in germ-line junctophilin-2 (JPH2) knockout mice, it has remained unclear whether JPH2 plays an essential role in junctional membrane complex formation and the Ca 2+ -induced Ca 2+ release process in the heart. Our recent work demonstrated loss-of-function mutations in JPH2 in patients with hypertrophic cardiomyopathy. Methods and Results— To elucidate the role of JPH2 in the heart, we developed a novel approach to conditionally reduce JPH2 protein levels using RNA interference. Cardiac-specific JPH2 knockdown resulted in impaired cardiac contractility, which caused heart failure and increased mortality. JPH2 deficiency resulted in loss of excitation-contraction coupling gain, precipitated by a reduction in the number of junctional membrane complexes and increased variability in the plasmalemma–sarcoplasmic reticulum distance. Conclusions— Loss of JPH2 had profound effects on Ca 2+ release channel inactivation, suggesting a novel functional role for JPH2 in regulating intracellular Ca 2+ release channels in cardiac myocytes. Thus, our novel approach of cardiac-specific short hairpin RNA–mediated knockdown of junctophilin-2 has uncovered a critical role for junctophilin in intracellular Ca 2+ release in the heart.

A recently identified variant within the fat mass and obesity-associated ( FTO ) gene is carried by 46% of Western Europeans and is associated with an ~1.2 kg higher weight, on average, in adults and an ~1 cm greater waist circumference. With >1 billion overweight and 300 million obese persons worldwide, it is crucial to understand the implications of carrying this very common allele for the health of our aging population. FTO is highly expressed in the brain and elevated body mass index (BMI) is associated with brain atrophy, but it is unknown how the obesity-associated risk allele affects human brain structure. We therefore generated 3D maps of regional brain volume differences in 206 healthy elderly subjects scanned with MRI and genotyped as part of the Alzheimer's Disease Neuroimaging Initiative. We found a pattern of systematic brain volume deficits in carriers of the obesity-associated risk allele versus noncarriers. Relative to structure volumes in the mean template, FTO risk allele carriers versus noncarriers had an average brain volume difference of ~8% in the frontal lobes and 12% in the occipital lobes—these regions also showed significant volume deficits in subjects with higher BMI. These brain differences were not attributable to differences in cholesterol levels, hypertension, or the volume of white matter hyperintensities; which were not detectably higher in FTO risk allele carriers versus noncarriers. These brain maps reveal that a commonly carried susceptibility allele for obesity is associated with structural brain atrophy, with implications for the health of the elderly.

Abstract Background: Glomerular filtration rate (GFR) can be determined by measuring renal clearance of the radiocontrast agent iothalamate. Current analytic methods for quantifying iothalamate concentrations in plasma and urine using liquid chromatography or capillary electrophoresis have limitations such as long analysis times and susceptibility to interferences. We developed a liquid chromatography–tandem mass spectrometry (LC-MS/MS) method to overcome these limitations. Methods: Urine and plasma samples were deproteinized using acetonitrile and centrifugation. The supernatant was diluted in water and analyzed by LC-MS/MS using a water:methanol gradient. We monitored 4 multiple reaction monitoring transitions: m/z 614.8–487.0, 614.8–456.0, 614.8–361.1, and 614.8–177.1. We compared the results to those obtained via our standard capillary electrophoresis (CE-UV) on samples from 53 patients undergoing clinical GFR testing. Results: Mean recovery was 90%–110% in both urine and plasma matrices. Imprecision was ≤15% for the m/z 614.8–487.0 and 614.8–456.0 transitions over a 10-day period at 1 mg/L. Method comparison for 159 patient samples (53 clearances) provided the following Passing–Bablok regressions: plasma iothalamate LC-MS/MS (y) vs CE-UV (x), y = 0.99x + 0.36; urine iothalamate LC-MS/MS vs CE-UV, y = 1.01x + 0.31; corrected GFR LC-MS/MS vs CE-UV, y = 1.00x + 0.00. Interfering substances prevented accurate iothalamate quantification by CE-UV in 2 patients, whereas these samples could be analyzed by LC-MS/MS. Conclusions: Iothalamate can be quantified by LC-MS/MS for GFR measurement. This method circumvents potential problems with interfering substances that occasionally confound accurate GFR determinations.