Ritz says that having a team capable of bridging population studies and applied experiments was essential for her research on pesticide exposure and Parkinson’s disease. She also notes the importance of cross-disciplinary work. “Many of my ideas for hypotheses have come from other fields,” she says.
(Photo courtesy of Beate Ritz)
NIEHS grantee Beate Ritz, M.D.,
Ph.D., uses geographic information systems (GIS) technology to study links
between pesticide exposure and risk for Parkinson’s disease. Her research is
uncovering important gene-environment interactions - that is, the ways in which
genetic background and environmental exposures can influence a person’s
susceptibility to disease.
Understanding why some people who
are exposed to pesticides don't get Parkinson's disease could help us to
understand how to boost protective biological processes and to identify
preventive actions.
“Understanding why some people
who are exposed to pesticides don't get Parkinson's disease could help us to
understand how to boost protective biological processes and to identify
preventive actions,” says Ritz, who co-directs the University of California,
Los Angeles (UCLA) Center for Gene-Environment Studies in Parkinson's Disease.
“It could also help us find treatments for those at risk and help identify
stressors that come together to make people more vulnerable.”
GIS Image #1: The researchers used GIS techniques to create maps showing areas of pesticide application around a town (red equals higher poundage per acre than pink).
(Photo courtesy of Beate Ritz)
Mapping Exposure
Population studies involving pesticide exposures have
traditionally relied on study participants to self-report their pesticide use,
a method fraught with recall-related issues. For a more quantitative picture of
exposure, Ritz and her colleagues developed a way to integrate data collected
during 30 years of state-mandated pesticide reporting in California using a
GIS-based approach. The GIS method created detailed maps of pesticide exposure
for each person, and adding a time component provided exposure information for
the home and workplace over much of a person’s life.
They used this method to examine
pesticide use and Parkinson’s disease in California’s Central Valley, a rural
region where people live close to fields with extensive agricultural pesticide
application. In one study, the researchers estimated pesticide exposure from
well water with the GIS tool. They found that possible well water contamination
with high levels of methomyl, chlorpyrifos, and propargite pesticides resulted
in an approximately 70 to 90% increase in risk of Parkinson’s disease compared
with residents that were not exposed to these contaminants in well water.
In another study, they estimated
exposure to airborne ziram, maneb, and paraquat pesticides at workplaces and
residences. Exposure to the combination of these three pesticides led to a
greater risk of Parkinson’s disease than each alone, with people exposed both
at work and at home having the highest risk.
GIS Image #2: The researchers used GIS techniques to create maps showing areas of pesticide application around a town (red equals higher poundage per acre than pink).
(Photo courtesy of Beate Ritz)
(Photo courtesy of Beate Ritz)
Gene-environment Interactions
The researchers took the
pesticide exposure stories unveiled by the GIS method a step farther and looked
for variations in gene sequences that make people more susceptible to
Parkinson’s disease when exposed to pesticides.
“The challenge of identifying gene-environment interactions is
to measure the environmental exposures reliably and to find the right genes to
study,” says Ritz, who is a professor and vice chair of the UCLA Epidemiology
Department. “Many studies today have a hard time assessing exposures, and you
have to know something about the biology to know what genes to examine.”
The researchers focused on genes involved
in risk for inherited forms of Parkinson’s disease, genes coding for enzymes
that metabolize contaminants into less toxic forms, and genes likely to be
affected by pesticides. “If we hypothesize that a pesticide causes Parkinson’s
disease through a specific mechanism and find that the pesticide affects people
more strongly who have a mutation in a gene involved in this pathway, this
helps show that it is the pesticide leading to the increased Parkinson’s
disease risk and not some other confounding factor,” she says.
So far, Ritz’s research has shown that increases in Parkinson’s
disease risk after pesticide exposure are associated with variations in the
paraoxonase 1 (PON1) and dopamine transporter (DAT) genes. Paraoxonase 1 breaks
down organophosphate pesticides that enter the body. DAT plays a central role
in neurotransmission, and mutations in the DAT gene might be involved in
Parkinson’s disease.
http://www.niehs.nih.gov/research/supported/success/ritz/
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