Childhood exposure to non-persistent endocrine disrupting chemicals and multi-omic profiles: A panel study.

BACKGROUND: Individuals are exposed to environmental pollutants with endocrine disrupting activity (endocrine disruptors, EDCs) and the early stages of life are particularly susceptible to these exposures. Previous studies have focused on identifying molecular signatures associated with EDCs, but none have used repeated sampling strategy and integrated multiple omics. We aimed to identify multi-omic signatures associated with childhood exposure to non-persistent EDCs. METHODS: We used data from the HELIX Child Panel Study, which included 156 children aged 6 to 11. Children were followed for one week, in two time periods. Twenty-two non-persistent EDCs (10 phthalate, 7 phenol, and 5 organophosphate pesticide metabolites) were measured in two weekly pools of 15 urine samples each. Multi-omic profiles (methylome, serum and urinary metabolome, proteome) were measured in blood and in a pool urine samples. We developed visit-specific Gaussian Graphical Models based on pairwise partial correlations. The visit-specific networks were then merged to identify reproducible associations. Independent biological evidence was systematically sought to confirm some of these associations and assess their potential health implications. RESULTS: 950 reproducible associations were found among which 23 were direct associations between EDCs and omics. For 9 of them, we were able to find corroborating evidence from previous literature: DEP - serotonin, OXBE - cg27466129, OXBE - dimethylamine, triclosan - leptin, triclosan - serotonin, MBzP - Neu5AC, MEHP - cg20080548, oh-MiNP - kynurenine, oxo-MiNP - 5-oxoproline. We used these associations to explore possible mechanisms between EDCs and health outcomes, and found links to health outcomes for 3 analytes: serotonin and kynurenine in relation to neuro-behavioural development, and leptin in relation to obesity and insulin resistance. CONCLUSIONS: This multi-omics network analysis at two time points identified biologically relevant molecular signatures related to non-persistent EDC exposure in childhood, suggesting pathways related to neurological and metabolic outcomes.

A novel whole blood gene expression signature for asthma, dermatitis, and rhinitis multimorbidity in children and adolescents.

BACKGROUND: Allergic diseases often occur in combination (multimorbidity). Human blood transcriptome studies have not addressed multimorbidity. Large-scale gene expression data were combined to retrieve biomarkers and signaling pathways to disentangle allergic multimorbidity phenotypes. METHODS: Integrated transcriptomic analysis was conducted in 1233 participants with a discovery phase using gene expression data (Human Transcriptome Array 2.0) from whole blood of 786 children from three European birth cohorts (MeDALL), and a replication phase using RNA Sequencing data from an independent cohort (EVA-PR, n = 447). Allergic diseases (asthma, atopic dermatitis, rhinitis) were considered as single disease or multimorbidity (at least two diseases), and compared with no disease. RESULTS: Fifty genes were differentially expressed in allergic diseases. Thirty-two were not previously described in allergy. Eight genes were consistently overexpressed in all types of multimorbidity for asthma, dermatitis, and rhinitis (CLC, EMR4P, IL5RA, FRRS1, HRH4, SLC29A1, SIGLEC8, IL1RL1). All genes were replicated the in EVA-PR cohort. RT-qPCR validated the overexpression of selected genes. In MeDALL, 27 genes were differentially expressed in rhinitis alone, but none was significant for asthma or dermatitis alone. The multimorbidity signature was enriched in eosinophil-associated immune response and signal transduction. Protein-protein interaction network analysis identified IL5/JAK/STAT and IL33/ST2/IRAK/TRAF as key signaling pathways in multimorbid diseases. Synergistic effect of multimorbidity on gene expression levels was found. CONCLUSION: A signature of eight genes identifies multimorbidity for asthma, rhinitis, and dermatitis. Our results have clinical and mechanistic implications, and suggest that multimorbidity should be considered differently than allergic diseases occurring alone.

A pooling-based genome-wide analysis identifies new potential candidate genes for atopy in the European Community Respiratory Health Survey (ECRHS).

BACKGROUND: Asthma and atopy are complex phenotypes with shared genetic component. In this study we attempt to identify genes related to these traits performing a two-stage DNA pooling genome-wide analysis in order to reduce costs. First, we assessed all markers in a subset of subjects using DNA pooling, and in a second stage we evaluated the most promising markers at an individual level. METHODS: For the genome-wide analysis, we constructed DNA pools from 75 subjects with atopy and asthma, 75 subjects with atopy and without asthma and 75 control subjects without atopy or asthma. In a second stage, the most promising regions surrounding significant markers after correction for false discovery rate were replicated with individual genotyping of samples included in the pools and an additional set of 429 atopic subjects and 222 controls from the same study centres. RESULTS: Homo sapiens protein kinase-like protein SgK493 (SGK493) was found to be associated with atopy. To lesser extent mitogen-activated protein kinase 5 (MAP3K5), collagen type XVIII alpha 1 (COL18A1) and collagen type XXIX alpha 1 (COL29A1) were also found to be associated with atopy. Functional evidences points out a role for MAP3K5, COL18A1 and COL29A1 but the function of SGK493 is unknown. CONCLUSION: In this analysis we have identified new candidate regions related to atopy and suggest SGK493 as an atopy locus, although these results need further replication.