Here our aim was to study whether it is possible to separate different genetic cardiac diseases (CPVT, LQT, HCM) on the basis of Ca<sup>2+</sup> transients using machine learning methods.
Mutations that map to the KvLQT1 and minK genes account for more than 50% of an inherited cardiac disorder, the Long QT syndrome (Splawski, I., Tristani-Firouzi, M., Lehmann, M. H., Sanguinetti, M. C., and Keating, M. T. (1997) Nat.Genet.17, 338-340).
The purpose of this study was to evaluate serum gastrin levels, as a surrogate for impaired gastric acid secretion, in patients with KCNQ1 mutations, and to see if gastrin levels correlate with severity of cardiac disease.