night shift work; nurses; targeted metabolomics; Tobit regression; machine-learning; Random Forest; occupational health
Abstract :
[en] Background and aim: Shift work, especially including night shifts, has been found associated with several diseases, including obesity, diabetes, cancers, and cardiovascular, mental, gastrointestinal and sleep disorders. Metabolomics (an omics-based methodology) may shed light on early biological alterations underlying these associations. We thus aimed to evaluate the effect of night shift work (NSW) on serum metabolites in a sample of hospital female nurses.
Methods: We recruited 46 nurses currently working in NSW in Milan (Italy), matched to 51 colleagues not employed in night shifts. Participants filled in a questionnaire on demographics, lifestyle habits, personal and family health history and work, and donated a blood sample. The metabolome was evaluated through a validated targeted approach measuring 188 metabolites. Only metabolites with at least 50% observations above the detection limit were considered, after standardization and log-transformation. Associations between each metabolite and NSW were assessed applying Tobit regression models and Random Forest, a machine-learning algorithm.
Results: When comparing current vs. never night shifters, we observed lower levels of 21 glycerophospholipids and 6 sphingolipids, and higher levels of serotonin (+171.0%, 95%CI: 49.1–392.7), aspartic acid (+155.8%, 95%CI: 40.8–364.7), and taurine (+182.1%, 95%CI: 67.6–374.9). The latter was higher in former vs. never night shifters too (+208.8%, 95%CI: 69.2–463.3). Tobit regression comparing ever (i.e., current + former) and never night shifters returned similar results. Years worked in night shifts did not seem to affect metabolite levels. The Random-Forest algorithm confirmed taurine and aspartic acid among the most important variables in discriminating current vs. never night shifters.
Conclusions: This study, although based on a small sample size, shows altered levels of some metabolites in night shift workers. If confirmed, our results may shed light on early biological alterations that might be related to adverse health effects of NSW.
Disciplines :
Public health, health care sciences & services
Author, co-author :
Borroni, Elisa ✱; University of Milan > Department of Clinical Sciences and Community Health
Frigerio, Gianfranco ✱; University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Environmental Cheminformatics
Polledri, Elisa
Mercadante, Rosa
Maggioni, Cristina; University of Milan > Department of Clinical Sciences and Community Health
Fedrizzi, Luca; Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico > Occupational Health Unit
Pesatori, Angela Cecilia; University of Milan > Department of Clinical Sciences and Community Health
Fustinoni, Silvia; University of Milan > Department of Clinical Sciences and Community Health
Carugno, Michele; University of Milan > Department of Clinical Sciences and Community Health
✱ These authors have contributed equally to this work.
External co-authors :
yes
Language :
English
Title :
Metabolomic profiles in night shift workers: A cross-sectional study on hospital female nurses
This research was funded by the University of Milan (UNIMI - Piano Sostegno alla Ricerca Anno 2019 - Linea 2). GF was currently supported by the Luxembourg National Research Fund (FNR) for project A18/BM/12341006. ACP was supported by the FNR.
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