Joint and interactive effects between health comorbidities and environmental exposures in predicting amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a rare yet devastating neurodegenerative condition. The mechanisms leading to ALS are most certainly complex and likely involve a joint contribution of several factors with possible synergistic or antagonistic interactions. To provide a better understanding of the association between non-genetic factors and ALS, we evaluated the joint exposure to multiple health and environmental factors linked with ALS in our previous studies, also screening for high-dimensional interactions. We used data from a nested case-control study within the Danish population, with 1086 ALS cases from 1982 to 2009, jointly investigating 4 hospital-based diagnoses - diabetes, obesity, physical/stress trauma, cardiovascular disease (CVD) during 1977–2009; and 4 environmental exposures - lead, formaldehyde, diesel exhaust, and solvents, assessed from individual occupational history. All covariates were evaluated as ever/never exposed, and we used targeted machine learning techniques to screen for important joint predictors and interactions. These were then evaluated in a final logistic regression model adjusting for potential confounders (age, SES, geography). All analyses were stratified by sex. Among men, trauma and solvents were associated with higher odds of ALS (OR = 1.55, 95% CI: 1.08–2.23; OR = 1.49, 95% CI: 1.17–1.89, respectively), and presented a negative interaction (OR = 0.49, 95% CI: 0.30–0.80). A positive diesel/CVD interaction was observed (OR = 1.56, 95% CI: 0.94–2.60). Among women, solvents, trauma, lead, and CVD were associated with higher odds of ALS, and a negative lead/solvents interaction was documented (OR = 0.52, 95% CI: 0.42–0.63). This study is one of the first attempts to evaluate joint and interactive effects of multiple risk factors on ALS, identifying potential synergistic and antagonistic mechanisms.