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Modification Effect of PARP4 and ERCC1 Gene Polymorphisms on the Relationship between Particulate Matter Exposure and
Jin Hee Kim1, Seungho Lee2, Yun-Chul Hong3
1Department of Integrative Bioscience & Biotechnology, Sejong University, 209 Neungdong-ro, Gwangjin-gu, Seoul 05006, Korea.
Abstract:
Particulate matter (PM) has been linked to adverse health outcomes, including insulin resistance (IR). To evaluate the relationships between exposures to PM10, PM2.5-10, and PM2.5; 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 PM10, PM2.5-10, and PM2.5 during the study period were 43.4 µg/m3, 19.9 µg/m3, and 23.6 µg/m3, respectively. All three PMs on lag day 4 (mean, 44.5 µg/m3 for PM10, 19.9 µg/m3 for PM2.5-10, and 24.3 µg/m3 for PM2.5) 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 PM10; β = 3.0 and p = 0.0010 for PM2.5-10; and β = 2.0 and p = 0.0134 for PM2.5). 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 PM10, β = 3.5 and p = 0.0009 for PM2.5-10, and β = 1.6 and p = 0.0020 for PM2.5; ERCC1 T-C: β = 2.2 and p = 0.0016 for PM10, β = 3.5 and p = 0.0003 for PM2.5-10, and β = 1.2 and p = 0.0158 for PM2.5). Our results indicated that genetic polymorphisms of PARP4 and ERCC1 could modify the relationship between PMs exposure and fasting glucose level in the elderly.
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