Abstract
BACKGROUND: Smoking and depression often co-occur in young adults, potentially due to reciprocal causal effects and/or shared underlying etiological factors. Here, we tested causal hypotheses between smoking quantity (cigarettes per day; CigDay ) and depressive symptoms ( DepSx ) using novel Biometrical Cross-Lagged Panel Models (CLPMs), which integrate twin developmental and direction-of-causation analyses for more robust causal inference in longitudinal twin studies. METHODS: Study sample included 10,034 participants (61.6% females; 4,112 twin pairs) from the Twins Early Development Study, with up to six repeated assessments spanning ages 21-29. The Biometrical CLPM provided three key innovations over standard twin CLPM: distinct autoregressive processes of latent genetic and environmental factors; cross-lagged genetic and environmental liabilities, contrasting confounding and causation; and cross-sectional causal effects, distinguishing between proximal (short-term) and distal (lagged) causation. RESULTS: In the two largest waves assessed approximately four years apart, genetic liabilities for both variables remained highly stable, while environmental influences showed considerable temporal variation. In the standard CLPM, CigDay predicted DepSx four years later. However, in the Biometrical CLPM, the cross-lagged phenotypic associations were attenuated and non-significant when accounting for the differential genetic and environmental developmental processes. Adding the cross-sectional causal paths revealed significant bidirectional proximal effects, with a stronger CigDay→DepSx effect. Across all six waves with intervals up to two years, analyses consistently showed significant bidirectional cross-lagged associations. CONCLUSIONS: The findings support a reinforcing feedback loop between CigDay and DepSx during young adulthood, involving bidirectional effects that persist for up to two years but dissipate over longer intervals.