Login / Signup

Contribution of Solar Radiation and Pollution to Parkinson's Disease.

Isabella KarakisShaked YarzaYair ZlotnikGal IferganeItai KloogKineret Grant-SassonLena Novack
Published in: International journal of environmental research and public health (2023)
Background . Parkinson's disease (PD) is believed to develop from epigenetic modulation of gene expression through environmental factors that accounts for up to 85% of all PD cases. The main objective of this study was to examine the association between PD onset and a cumulative exposure to potentially modifiable ambient exposures. Methods . The study population comprised 3343 incident PD cases and 31,324 non-PD controls in Southern Israel. The exposures were determined based on the monitoring stations and averaged per year. Their association with PD was modeled using a distributed lag non-linear model and presented as an effect of exposure to the 75th percentile as compared to the 50th percentile of each pollutant, accumulated over the span of 5 years prior to the PD. Results . We recorded an adverse effect of particulate matter of size ≤10 μm in diameter (PM 10 ) and solar radiation (SR) with odds ratio (OR) = 1.06 (95%CI: 1.02; 1.10) and 1.23 (95%CI: 1.08; 1.39), respectively. Ozone (O 3 ) was also adversely linked to PD, although with a borderline significance, OR: 1.12 (95%CI: 0.99; 1.25). Immigrants arriving in Israel after 1989 appeared to be more vulnerable to exposure to O 3 and SR. The dose response effect of SR, non-existent for Israeli-born (OR = 0.67, 95%CI: 0.40; 1.13), moderate for immigrants before 1989 (OR = 1.17, 95%CI: 0.98; 1.40) and relatively high for new immigrants (OR = 1.25, 95%CI: 1.25; 2.38) indicates an adaptation ability to SR. Conclusions . Our findings supported previous reports on adverse association of PD with exposure to PM 10 and O 3 . Additionally, we revealed a link of Parkinson's Disease with SR that warrants an extensive analysis by research groups worldwide.
Keyphrases
  • particulate matter
  • air pollution
  • gene expression
  • dna methylation
  • type diabetes
  • heavy metals
  • nitric oxide
  • high intensity
  • polycyclic aromatic hydrocarbons
  • data analysis