OBJECTIVE: We hypothesized that Cav1.3 blockade by cinnarizine may achieve similar, or greater, reduction in aldosterone secretion than nonselective Cav1.2/1.3 blockade by nifedipine.
METHODS: Separate wells of angiotensin II-stimulated HAC15 cells were treated with either cinnarizine (1-30 μM) or nifedipine (1-100 μM). Aldosterone concentrations were measured in culture medium; RNA extraction and quantitative polymerase chain reaction were performed to evaluate CYP11B2 expression. A prospective, open-label, crossover study was conducted of 15 adults with PA, treated with 2 weeks of cinnarizine 30 mg 3 times a day or nifedipine extended release 60 mg daily, separated by a 2-week washout. The hierarchical primary outcome was change in aldosterone-to-renin ratio (ARR), urinary tetrahydroaldosterone (THA), and plasma aldosterone concentration (PAC). Blood pressure change was a secondary outcome. Parametric analysis was undertaken on log-transformed data. (ClinicalTrials.gov: NCT05686993).
RESULTS: Both drugs reduced aldosterone concentrations and CYP11B2 expression in vitro. Mean changes ± SEM in fold change of aldosterone concentrations and CYP11B2 were -0.47 ± 0.05 and -0.56 ± 0.07, respectively, with cinnarizine 30 μM and -0.59 ± 0.05 and -0.78 ± 0.07 with nifedipine 100 μM. In the clinical crossover trial, ARR was reduced by nifedipine but not cinnarizine (F = 3.25; P = .047); PAC rose with both drugs (F = 4.77; P = .013), but urinary THA was unchanged.
CONCLUSION: A Cav1.3 ligand, cinnarizine, reduced aldosterone secretion from adrenocortical cells, but at maximum-soluble concentrations was less effective than the nonselective calcium blocker, nifedipine. At clinical doses, cinnarizine did not reduce plasma ARR in patients with PA, and, as in vitro, was inferior to nifedipine. The limited efficacy of high-dose nifedipine may be due to incomplete Cav1.3 blockade, or to a role for non-L-type calcium channels in aldosterone secretion.
RESULTS: Important issues were identified during the data harmonisation process relating to data ownership, sharing methodologies and ethical concerns. Measures were assessed across eight domains; demographic; dietary; clinical and anthropometric; medical history; hypertension knowledge; physical activity; behavioural (smoking and alcohol); and biochemical domains. Identifying validated measures relevant across a variety of settings presented some difficulties. The resulting GACD hypertension data dictionary comprises 67 consensus measures. Of the 14 responding teams, only two teams were including more than 50 consensus variables, five teams were including between 25 and 50 consensus variables and four teams were including between 6 and 24 consensus variables, one team did not provide details of the variables collected and two teams did not include any of the consensus variables as the project had already commenced or the measures were not relevant to their study.
CONCLUSIONS: Deriving consensus measures across diverse research projects and contexts was challenging. The major barrier to their implementation was related to the time taken to develop and present these measures. Inclusion of consensus measures into future funding announcements would facilitate researchers integrating these measures within application protocols. We suggest that adoption of consensus measures developed here, across the field of hypertension, would help advance the science in this area, allowing for more comparable data sets and generalizable inferences.