Modification Effect of PARP4 and ERCC1 Gene Polymorphisms on the Relationship between Particulate Matter Exposure and Fasting Glucose Level.
Jin Hee KimSeungho LeeYun-Chul HongPublished in: International journal of environmental research and public health (2022)
Particulate matter (PM) has been linked to adverse health outcomes, including insulin resistance (IR). To evaluate the relationships between exposures to PM 10 , PM 2.5-10 , and PM 2.5 ; the serum level of fasting glucose, a key IR indicator; and effects of polymorphisms of two repair genes ( PARP4 and ERCC1 ) on these relations, PMs exposure data and blood samples for glucose measurement and genotyping were collected from 527 Korean elders. Daily average levels of PMs during 8 days, from 7 days before examination to the health examination day (from lag day 7 to lag day 0), were used for association analyses, and mean concentrations of PM 10 , PM 2.5-10 , and PM 2.5 during the study period were 43.4 µg/m 3 , 19.9 µg/m 3 , and 23.6 µg/m 3 , respectively. All three PMs on lag day 4 (mean, 44.5 µg/m 3 for PM 10 , 19.9 µg/m 3 for PM 2.5-10 , and 24.3 µg/m 3 for PM 2.5 ) were most strongly associated with an increase in glucose level (percent change by inter-quartile range-change of PM: (β) = 1.4 and p = 0.0023 for PM 10 ; β = 3.0 and p = 0.0010 for PM 2.5-10 ; and β = 2.0 and p = 0.0134 for PM 2.5 ). In particular, elders with PARP4 G-C-G or ERCC1 T-C haplotype were susceptible to PMs exposure in relation to glucose levels ( PARP4 G-C-G: β = 2.6 and p = 0.0006 for PM 10 , β = 3.5 and p = 0.0009 for PM 2.5-10 , and β = 1.6 and p = 0.0020 for PM 2.5 ; ERCC1 T-C: β = 2.2 and p = 0.0016 for PM 10 , β = 3.5 and p = 0.0003 for PM 2.5-10 , and β = 1.2 and p = 0.0158 for PM 2.5 ). Our results indicated that genetic polymorphisms of PARP4 and ERCC1 could modify the relationship between PMs exposure and fasting glucose level in the elderly.
Keyphrases
- particulate matter
- air pollution
- polycyclic aromatic hydrocarbons
- heavy metals
- insulin resistance
- water soluble
- blood glucose
- healthcare
- dna damage
- mental health
- machine learning
- skeletal muscle
- genome wide
- dna methylation
- polycystic ovary syndrome
- oxidative stress
- transcription factor
- human health
- high throughput
- artificial intelligence