Ca²⁺ currents in cardiomyocytes: How to improve interpretation of patch clamp data?

Variability of ion currents is major issue when used for significance testing. One of the simplest approach to reduce variability is normalization to cell membrane size. However, efficacy of Ca²⁺ currents (I_Ca) normalization is unknown. Beside absolute variability, the type of distribution since non-Gaussian distribution makes application of nonparametric test necessary.

We retrospectively analyzed individual I_Ca amplitudes measured in ventricular cardiomyocytes from mice, rats and humans and in atrial cardiomyocytes from humans in sinus rhythm and in atrial fibrillation. I_Ca was normalized to cell membrane size, estimated from capacitance transients. In addition, data were Log transformed to reach Gaussian distribution. Normalized and transformed data were analyzed for variability and applicability of parametric vs. nonparametric tests.

There was strong correlation between I_Ca and cell membrane size. However, correlation coefficient was rather low. Normalizing I_Ca had an inconsistent effect on variability. Variability of I_Ca in cells from the same patient/animal was not different cardiomyocytes from humans, rat and mice. Calculation of mean values based on mean values of cells from individuals (patients or animals) vs. mean values calculated for all cells drastically reduces statistical power to detect differences between the groups. Log transformation of I_Ca allowed application of much higher sensitive parametric testing, compensating loss of power.

Impact of cell membrane size to I_Ca is low and may limit efficacy of normalization of I_Ca to reduce variability. In contrast, Log transformation of I_Ca data reduces variability and can increase statistical power to detect difference between I_Ca datasets.