Dataset Information

Gene-environment interactions increase the risk of paediatric-onset multiple sclerosis associated with household chemical exposures.

ABSTRACT:

Background

We previously reported an association between household chemical exposures and an increased risk of paediatric-onset multiple sclerosis.

Methods

Using a case-control paediatric multiple sclerosis study, gene-environment interaction between exposure to household chemicals and genotypes for risk of paediatric-onset multiple sclerosis was estimated.Genetic risk factors of interest included the two major HLA multiple sclerosis risk factors, the presence of DRB1*15 and the absence of A*02, and multiple sclerosis risk variants within the metabolic pathways of common household toxic chemicals, including IL-6 (rs2069852), BCL-2 (rs2187163) and NFKB1 (rs7665090).

Results

490 paediatric-onset multiple sclerosis cases and 716 controls were included in the analyses. Exposures to insect repellent for ticks or mosquitos (OR 1.47, 95% CI 1.06 to 2.04, p=0.019), weed control products (OR 2.15, 95% CI 1.51 to 3.07, p<0.001) and plant/tree insect or disease control products (OR 3.25, 95% CI 1.92 to 5.49, p<0.001) were associated with increased odds of paediatric-onset multiple sclerosis. There was significant additive interaction between exposure to weed control products and NFKB1 SNP GG (attributable proportions (AP) 0.48, 95% CI 0.10 to 0.87), and exposure to plant or disease control products and absence of HLA-A*02 (AP 0.56; 95% CI 0.03 to 1.08). There was a multiplicative interaction between exposure to weed control products and NFKB1 SNP GG genotype (OR 2.30, 95% CI 1.00 to 5.30) but not for other exposures and risk variants. No interactions were found with IL-6 and BCL-2 SNP GG genotypes.

Conclusions

The presence of gene-environment interactions with household toxins supports their possible causal role in paediatric-onset multiple sclerosis.

SUBMITTER: Nasr Z

PROVIDER: S-EPMC10272045 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature

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Publications

Gene-environment interactions increase the risk of paediatric-onset multiple sclerosis associated with household chemical exposures.

Nasr Zahra Z Nasr Zahra Z Schoeps Vinicius Andreoli VA Ziaei Amin A Virupakshaiah Akash A Adams Cameron C Casper T Charles TC Waltz Michael M Rose John J Rodriguez Moses M Tillema Jan-Mendelt JM Chitnis Tanuja T Graves Jennifer S JS Benson Leslie L Rensel Mary M Krupp Lauren L Waldman Amy T AT Weinstock-Guttman Bianca B Lotze Tim T Greenberg Benjamin B Aaen Gregory G Mar Soe S Schreiner Teri T Hart Janace J Simpson-Yap Steve S Mesaros Clementina C Barcellos Lisa F LF Waubant Emmanuelle E

Journal of neurology, neurosurgery, and psychiatry 20230201 7

<h4>Background</h4>We previously reported an association between household chemical exposures and an increased risk of paediatric-onset multiple sclerosis.<h4>Methods</h4>Using a case-control paediatric multiple sclerosis study, gene-environment interaction between exposure to household chemicals and genotypes for risk of paediatric-onset multiple sclerosis was estimated.Genetic risk factors of interest included the two major HLA multiple sclerosis risk factors, the presence of <i>DRB1*15</i> an ...[more]

PMID: 36725329

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Project description:BackgroundWe previously reported a relationship between air pollutants and increased risk of pediatric-onset multiple sclerosis (POMS). Ozone is an air pollutant that may play a role in multiple sclerosis (MS) pathoetiology. CD86 is the only non-HLA gene associated with POMS for which expression on antigen-presenting cells (APCs) is changed in response to ozone exposure.ObjectivesTo examine the association between county-level ozone and POMS, and the interactions between ozone pollution, CD86, and HLA-DRB1*15, the strongest genetic variant associated with POMS.MethodsCases and controls were enrolled in the Environmental and Genetic Risk Factors for Pediatric MS study of the US Network of Pediatric MS Centers. County-level-modeled ozone data were acquired from the CDC's Environmental Tracking Network. Participants were assigned ozone values based on county of residence. Values were categorized into tertiles based on healthy controls. The association between ozone tertiles and having MS was assessed by logistic regression. Interactions between tertiles of ozone level and the GG genotype of the rs928264 (G/A) single nucleotide polymorphism (SNP) within CD86, and the presence of DRB1*15:01 (DRB1*15) on odds of POMS were evaluated. Models were adjusted for age, sex, genetic ancestry, and mother's education. Additive interaction was estimated using relative excess risk due to interaction (RERI) and attributable proportions (APs) of disease were calculated.ResultsA total of 334 POMS cases and 565 controls contributed to the analyses. County-level ozone was associated with increased odds of POMS (odds ratio 2.47, 95% confidence interval (CI): 1.69-3.59 and 1.95, 95% CI: 1.32-2.88 for the upper two tertiles, respectively, compared with the lowest tertile). There was a significant additive interaction between high ozone tertiles and presence of DRB1*15, with a RERI of 2.21 (95% CI: 0.83-3.59) and an AP of 0.56 (95% CI: 0.33-0.79). Additive interaction between high ozone tertiles and the CD86 GG genotype was present, with a RERI of 1.60 (95% CI: 0.14-3.06) and an AP of 0.37 (95% CI: 0.001-0.75) compared to the lowest ozone tertile. AP results indicated that approximately half of the POMS risk in subjects can be attributed to the possible interaction between higher county-level ozone carrying either DRB1*15 or the CD86 GG genotype.ConclusionsIn addition to the association between high county-level ozone and POMS, we report evidence for additive interactions between higher county-level ozone and DRB1*15 and the CD86 GG genotype. Identifying gene-environment interactions may provide mechanistic insight of biological processes at play in MS susceptibility. Our work suggests a possible role of APCs for county-level ozone-induced POMS risk.

Project description:Elucidation of distinct T-cell subsets involved in multiple sclerosis immune-pathophysiology continues to be of considerable interest since an ultimate goal is to more selectively target the aberrant immune response operating in individual patients. While abnormalities of both effector (Teff) and regulatory (Treg) T cells have been reported in patients with multiple sclerosis, prior studies have mostly assessed average abnormalities in either limb of the immune response, rather than both at the same time, which limits the ability to evaluate the balance between effectors and regulators operating in the same patient. Assessing both phenotypic and functional responses of Teffs and Tregs has also proven important. In studies of adults with multiple sclerosis, in whom biological disease onset likely started many years prior to the immune assessments, an added challenge for any reported abnormality is whether the abnormality indeed contributes to the disease (and hence of interest to target therapeutically) or merely develops consequent to inflammatory injury (in which case efforts to develop targeted therapies are unlikely to be beneficial). Paediatric-onset multiple sclerosis, though rare, offers a unique window into early disease mechanisms. Here, we carried out a comprehensive integrated study, simultaneously assessing phenotype and functional responses of both effector and regulatory T cells in the same children with multiple sclerosis, monophasic inflammatory CNS disorders, and healthy controls, recruited as part of the multicentre prospective Canadian Pediatric Demyelinating Disease Study (CPDDS). Stringent standard operating procedures were developed and uniformly applied to procure, process and subsequently analyse peripheral blood cells using rigorously applied multi-parametric flow cytometry panels and miniaturized functional assays validated for use with cryopreserved cells. We found abnormally increased frequencies and exaggerated pro-inflammatory responses of CD8+CD161highTCR-Vα7.2+ MAIT T cells and CD4+CCR2+CCR5+ Teffs in paediatric-onset multiple sclerosis, compared to both control groups. CD4+CD25hiCD127lowFOXP3+ Tregs of children with multiple sclerosis exhibited deficient suppressive capacity, including diminished capacity to suppress disease-implicated Teffs. In turn, the implicated Teffs of multiple sclerosis patients were relatively resistant to suppression by normal Tregs. An abnormal Teff/Treg ratio at the individual child level best distinguished multiple sclerosis children from controls. We implicate abnormalities in both frequencies and functional responses of distinct pro-inflammatory CD4 and CD8 T cell subsets, as well as Treg function, in paediatric-onset multiple sclerosis, and suggest that mechanisms contributing to early multiple sclerosis development differ across individuals, reflecting an excess abnormality in either Teff or Treg limbs of the T cell response, or a combination of lesser abnormalities in both limbs.

Project description:Many existing cohort studies initially designed to investigate disease risk as a function of environmental exposures have collected genomic data in recent years with the objective of testing for gene-environment interaction (G × E) effects. In environmental epidemiology, interest in G × E arises primarily after a significant effect of the environmental exposure has been documented. Cohort studies often collect rich exposure data; as a result, assessing G × E effects in the presence of multiple exposure markers further increases the burden of multiple testing, an issue already present in both genetic and environment health studies. Latent variable (LV) models have been used in environmental epidemiology to reduce dimensionality of the exposure data, gain power by reducing multiplicity issues via condensing exposure data, and avoid collinearity problems due to presence of multiple correlated exposures. We extend the LV framework to characterize gene-environment interaction in presence of multiple correlated exposures and genotype categories. Further, similar to what has been done in case-control G × E studies, we use the assumption of gene-environment (G-E) independence to boost the power of tests for interaction. The consequences of making this assumption, or the issue of how to explicitly model G-E association has not been previously investigated in LV models. We postulate a hierarchy of assumptions about the LV model regarding the different forms of G-E dependence and show that making such assumptions may influence inferential results on the G, E, and G × E parameters. We implement a class of shrinkage estimators to data adaptively trade-off between the most restrictive to most flexible form of G-E dependence assumption and note that such class of compromise estimators can serve as a benchmark of model adequacy in LV models. We demonstrate the methods with an example from the Early Life Exposures in Mexico City to Neuro-Toxicants Study of lead exposure, iron metabolism genes, and birth weight.

Dataset Information

Gene-environment interactions increase the risk of paediatric-onset multiple sclerosis associated with household chemical exposures.

Background

Methods

Results

Conclusions

Publications

Gene-environment interactions increase the risk of paediatric-onset multiple sclerosis associated with household chemical exposures.

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