Genes + emissions: When Parkinson's disease risk multiplies

Parkinson's disease (PD) is a rapidly growing neurodegenerative disorder, the prevalence of which is increasing not only due to the aging population. It is based on a combination of genetic vulnerability and environmental factors. Monogenic forms are rare, but the combination of dozens of common DNA variations makes a significant contribution to the overall risk. The polygenic risk score (PRS) allows us to summarize this contribution and is used today as an integral measure of hereditary predisposition.

People with a high “polygenic rate” for Parkinson’s disease (PRS) and long-term exposure to traffic-related air pollution (TRAP) have the highest risk of developing the disease. In a meta-analysis of two population-based studies from California and Denmark (a total of 1,600 cases and 1,778 controls), the combination of high PRS and high TRAP resulted in a ~three-fold increase in the likelihood of Parkinson’s compared to the “low PRS + low TRAP” group. In other words, predisposition and environment work synergistically. The study was published in JAMA Network Open.

Background

Among environmental factors, the focus is on long-term exposure to “transport” air (TRAP): exhaust and wear particles (CO, NO₂/NOx, fine particles, PAHs). Accumulated evidence links living or working near heavy traffic with a higher risk of PD. Proposed mechanisms include neuroinflammation and oxidative stress, mitochondrial dysfunction, accumulation and pathological modification of α-synuclein, as well as penetration “routes” through the olfactory system and the respiratory tract; the “gut-brain” axis is also discussed.

However, three major gaps remained in the literature. First, many epidemiological studies assessed air exposure over relatively short periods (1–5 years), whereas the prodromal phase of PD extends over decades. Second, genetic analyses were often limited to individual candidate genes, underestimating the polygenic nature of vulnerability. Third, little study had been done on whether genetic risk amplifies harm from TRAP—that is, whether there is a significant gene×environment interaction.

Technologically, researchers have the tools to plug these holes: traffic dispersion models allow retrospective, address-based estimates of long-term exposure (with a reasonable lag to diagnosis), and PRS from large GWAS provides a robust metric of hereditary risk in populations of European descent. Using CO as a proxy for TRAP is justified in historical series: it is a direct marker of emissions, less susceptible to atmospheric chemistry, and is well validated near highways; at the same time, it is highly correlated with other transport contaminants.

From a scientific point of view, the key question is: does TRAP work “the same” for everyone, or does the same level of pollution lead to a disproportionately higher risk of PD in people with a high PRS? The answer is critical both for biology (understanding the mechanisms of vulnerability) and for public health: if synergy is found, then measures to reduce traffic pollution acquire a particularly high value for genetically vulnerable groups, and individual recommendations (routes, ventilation modes, air filtration) receive additional justification.

This is why the authors combined two independent population-based studies from different ecological and social contexts (Central California and Denmark), used long exposure windows with lags, confirmed PD diagnoses by specialists, and compared PRS with TRAP on a common scale. This design allows not only to assess the contribution of each factor, but also to test their interactions and “joint effects” — something that was missing in previous studies.

What's new and why is it important?

It has long been known that Parkinson's is influenced by both genes and the environment. Their individual contributions have been described: polygenic risk increases the chances of getting sick, and living near heavy traffic for years is associated with a higher risk. But there is little data on how they interact. The new study carefully tests this "linkage" for the first time in two countries at once, with long exposure windows and careful verification of diagnoses, and shows that high genetic risk makes air pollution significantly more dangerous.

How was it carried out?

• Design: Two independent population-based case-control studies + meta-analysis.
  • PEG (California): 634 patients with early Parkinson's disease, 733 controls.
  • PASIDA (Denmark): 966 cases, 1045 controls.
• Genes: Polygenic risk score (PRS) for 86 (alternatively 76) variations weighted by GWAS data. Expressed in SD (standard deviations).
• Pollution: long-term exposure to TRAP at home (main marker - CO as a proxy for emissions) according to dispersion models:
  • PEG: 10-year average with a 5-year lag to the index.
  • PASIDA: 15-year average with a 5-year lag.
• Statistics: logistic regression with adjustments (age, gender, education, smoking, family history, occupations with emissions, in PEG - pesticides; genetic components of population structure). PRS×TRAP interaction was tested and joint effects were plotted (low=q1–q3, high=q4).

Key numbers

• PRS by itself: for every +1 SD, the risk is 1.76 times higher (95% CI 1.63–1.90).
• TRAP itself: for every increase in IQR, the risk is 1.10 times higher (1.05–1.15).
• Interaction (multiplier): OR 1.06 (1.00–1.12). Small but significant in pooled data.
• Combined effect:
  • High PRS + high TRAP: OR 3.05 (2.23–4.19) vs. low+low.
  • This is higher than expected given the independent action of factors (expected ~2.80).

Translating from “statistical”: if a person has a high genetic risk, the same dose of road pollution will “hit” the brain harder.

How it can work

• Neuroinflammation and neurotoxicity: Exhaust emissions, particularly diesel particulates and polycyclic aromatic hydrocarbons, activate microglia, damage dopaminergic neurons, and enhance α-synuclein phosphorylation/accumulation.
• Portals of entry: olfactory bulb and respiratory tract; possible contribution from the gut and microbiota (gut-brain axis).
• Genes determine vulnerability: polygenic variations in the pathways of autophagy, mitochondria, and synaptic transmission make cells less resistant to the same inhalation stressors.

What does this mean for policy and practice?

For cities and regulators

• Clean transport: accelerate electrification, emission standards, smart low emission zones.
• Urban planning: green buffers, interchanges/screens, traffic redirection from housing and schools.
• Air monitoring: accessible micro-pollution maps; TRAP accounting in healthcare.

For clinicians

• In familial/early Parkinson's risk, it is reasonable to discuss avoiding high TRAP zones, especially in middle-old age.
• Factors that actually reduce the overall risk of neurodegeneration (activity, sleep, blood pressure/sugar control, smoking cessation) remain the base, and control of exposure to exhaust emissions is an addition to it.

For a person

• If possible, choose routes away from highways; ventilate with HEPA cleaning when there are traffic jams outside the window; do not run along busy roads during rush hour; use recirculation in the car in a traffic jam.

Important Disclaimers

• Case-control designs show associations, not causation.
• Exposure was modelled by residential address: no travel/work time taken into account → likely underestimation of effects.
• CO as a TRAP proxy is technically valid for emissions, but does not reflect all air chemistry.
• PRS of European ancestry: findings apply best to people of European ancestry; generalization to other populations requires testing.

Where to next?

• Expand PRS to different ethnic groups and test with other pollutants (NO₂, UFP, PM₂․₅/PM₁₀, black carbon).
• Prospective cohorts with personal sensors and inflammation/α-synuclein biomarkers.
• Assessing the benefits of interventions (air purifiers, routing, green barriers) specifically for people with high PRS.

Summary

Genetic predisposition to Parkinson's is not destiny, but when combined with long-term exposure to exhaust emissions, the risk increases significantly more than from each factor separately. This is an argument for a dual strategy: less exhaust for everyone and targeted prevention for the vulnerable.