Causal associations of sleep traits with cancer incidence and mortality

Front Genet. 2023 Nov 23:14:1309069. doi: 10.3389/fgene.2023.1309069. eCollection 2023.

Abstract

To explore the correlation and causality between multidimensional sleep traits and pan-cancer incidence and mortality among patients with cancer. The multivariable Cox regression, linear and nonlinear Mendelian randomization (MR), and survival curve analyses were conducted to assess the impacts of chronotype, sleep duration, and insomnia symptoms on pan-cancer risk (N = 326,417 from United Kingdom Biobank) and mortality (N = 23,956 from United Kingdom Biobank). In the Cox regression, we observed a linear and J-shaped association of sleep duration with pan-cancer incidence and mortality among cancer patients respectively. In addition, there was a positive association of insomnia with pan-cancer incidence (HR, 1.03, 95% CI: 1.00-1.06, p = 0.035), all-cause mortality (HR, 1.17, 95% CI: 1.06-1.30, p = 0.002) and cancer mortality among cancer patients (HR, 1.25, 95% CI: 1.11-1.41, p < 0.001). In the linear MR, there was supporting evidence of positive associations between long sleep duration and pan-cancer incidence (OR, 1.41, 95% CI: 1.08-1.84, p = 0.012), and there was a positive association between long sleep duration and all-cause mortality in cancer patients (OR, 5.56, 95% CI: 3.15-9.82, p = 3.42E-09). Meanwhile, a strong association between insomnia and all-cause mortality in cancer patients (OR, 1.41, 95% CI: 1.27-1.56, p = 4.96E-11) was observed in the linear MR. These results suggest that long sleep duration and insomnia play important roles in pan-cancer risk and mortality among cancer patients. In addition to short sleep duration and insomnia, our findings highlight the effect of long sleep duration in cancer prevention and prognosis.

Keywords: causal relationships; mendelian randomization; mortality; pan-cancer incidence; sleep traits.

Grants and funding

The authors declare financial support was received for the research, authorship, and/or publication of this article. This work was supported by the National Natural Science Foundation of China (no. 82203579, 82271528 and 82271527), the Peking University Sixth Hospital Scientific Research Cultivation Fund (no. PY21003), the National Key Research and Development Program of China (no. 2021YFC0863700), National Programs for Brain Science and Brain-like Intelligence Technology of China (no. 2021ZD0200800, 2021ZD0200700) and Science Foundation of Peking University Cancer Hospital (JC202304).