A case control study on the relationship between occupational stress and genetic polymorphism and dyslipidemia in coal miners

• Published in: Scientific reports Vol. 13; no. 1; p. 2321
• Main Authors: Yang, Yongzhong, Zheng, Ziwei, Chen, Yuanyu, Wang, Xuelin, Wang, Hui, Si, Zhikang, Meng, Rui, Wu, Jianhui
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 09-02-2023; Nature Publishing Group; Nature Portfolio
• Subjects: 631/208; 631/477; 692/1537; 692/499; Cardiovascular diseases; Case-Control Studies; China - epidemiology; Coal; Coal mining; Dyslipidemia; Dyslipidemias - epidemiology; Dyslipidemias - genetics; Environmental factors; Environmental regulations; Etiology; Gene polymorphism; Genetic factors; Genetic Predisposition to Disease; Genotype; Genotype & phenotype; Humanities and Social Sciences; Humans; Hypertension; Hyperuricemia; Metabolic disorders; MnSOD gene; multidisciplinary; Occupational health; Occupational Stress; Physical activity; Polymorphism, Genetic; Polymorphism, Single Nucleotide; Risk Factors; Science; Science (multidisciplinary); Shift work; Statistical analysis; Superoxide dismutase; China
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-023-29491-2

Dyslipidemia is one of the known risk factors for cardiovascular disease, and its prevalence is increasing worldwide. At present, the study of dyslipidemia has gradually shifted from simple environmental or genetic factors to environment-gene interactions. In order to further explore the etiology and mechanism of dyslipidemia, we used occupational stress(OS) and
LYPLAL1
,
APOC3
and
SOD2
gene as research variables to explore their association with dyslipidemia.Here we used a case-control study to include Han workers from a coal mining enterprise in China to determine the association between study variables and dyslipidemia. Monofactor analysis showed that smoking, drinking, physical activity level, DASH diet score, sleep quality, BMI, hypertension, hyperuricemia, shift work, OS were significantly different between the two groups (
P
 < 0.05). In the
APOC3
rs2854116 dominant model, patients with CT/CC genotype had a higher risk of dyslipidemia than those with TT genotype. In
SOD2
rs4880 recessive model, patients with GG genotype had a lower risk of dyslipidemia than those with AA/AG genotype, and the difference was statistically significant. We found that rs12137855 and OS, rs2854116 and OS, rs4880 and OS had joint effects, but no interaction based on the multiplication and addition model was found (
P
interaction
 > 0.05). GMDR model showed that the rs12137855-rs2854116-rs4880-OS four-factor model had the highest cross-validation consistency and training-validation accuracy (
P
 < 0.05), suggesting that there was a high-order interaction between them associated with dyslipidemia. We found that dyslipidemia in coal miners was related to OS and genetic factors. Through this study, we revealed the dual regulation of environmental factors and genetic factors on dyslipidemia. At the same time, this study provides clues for understanding the etiology and mechanism of dyslipidemia.