Many cardiovascular drugs have been implicated as causes of depression. With the exception of beta-blockers, few have been studied in formal epidemiologic designs. I present a new approach to such analyses that effectively controls for confounders that are stable over time. I analyzed the exposure histories of 11,244 incident antidepressant users, using the Odense University PharmacoEpidemiologic Database. All persons starting both beta-blockers and antidepressants during a predefined period were identified. If beta-blockers do not cause depression, this particular population should show equal numbers of persons starting either drug first. A depression-provoking effect of beta-blockers would generate an excess of persons starting beta-blockers first, that is a nonsymmetrical distribution of prescription orders. Confounders causing the two drugs to be co-prescribed would rarely be expected to affect the symmetry. The initial screening showed nonsymmetrical prescription orders for a wide range of cardiovascular drugs. After adjustment for an increasing incidence of antidepressant prescribing, I found a depression-provoking effect only for angiotensin-converting enzyme (ACE) inhibitors (rate ratio = 1.29; 95% confidence interval = 1.08-1.56) and calcium channel blockers (rate ratio = 1.31; 95% confidence interval = 1.14-1.51). This prescription sequence symmetry analysis may be useful as a screening tool.