Genetic variants altering cis-regulation of normal gene expression (cis-eQTLs) have been extensively mapped in human cells and tissues, but the extent by which controlled, environmental perturbation influences cis-eQTLs is unclear. We carried out large-scale induction experiments using primary human bone cells derived from unrelated donors of Swedish origin treated with 18 different stimuli (7 treatments and 2 controls, each assessed at 2 time points). The treatments with the largest impact on the transcriptome, verified on two independent expression arrays, included BMP-2 (t = 2h), dexamethasone (DEX) (t = 24h), and PGE₂ (t = 24h). Using these treatments and control, we performed expression profiling for 18,144 RefSeq transcripts on biological replicates of the complete study cohort of 113 individuals (n_total = 782) and combined it with genome-wide SNP-genotyping data in order to map treatment-specific cis-eQTLs (defined as SNPs located within the gene ±250 kb). We found that 93% of cis-eQTLs at 1% FDR were observed in at least one additional treatment, and in fact, on average, only 1.4% of the cis-eQTLs were considered as treatment-specific at high confidence. The relative invariability of cis-regulation following perturbation was reiterated independently by genome-wide allelic expression tests where only a small proportion of variance could be attributed to treatment. Treatment-specific cis-regulatory effects were, however, 2- to 6-fold more abundant among differently expressed genes upon treatment. We further followed-up and validated the DEX–specific cis-regulation of the MYO6 and TNC loci and found top cis-regulatory variants located 180 kb and 250 kb upstream of the transcription start sites, respectively. Our results suggest that, as opposed to tissue-specificity of cis-eQTLs, the interactions between cellular environment and cis-variants are relatively rare (∼1.5%), but that detection of such specific interactions can be achieved by a combination of functional genomic approaches as described here. Population variation in normal gene expression has been convincingly shown to be under strong genetic control where the main genetic variants are located within close proximity to the gene itself (so called cis-acting). However, the extent to which controlled, environmental stimuli influences cis-regulation of gene expression is unclear. Here, we combine different functional genomic approaches and examine the role of common genetic variants on induced gene expression in a population panel of primary human cells derived from ∼100 unrelated donors treated under multiple conditions. Using these approaches, we find that the interaction between cellular environment and cis-variants are relatively rare, with only a small proportion of the identified genetic variants being specific to treatment. However, although treatment-specific genetic regulation of gene expression seems to be infrequent, we prove its existence by thorough validation of treatment-specific effects of the glucocorticoid-specific regulation of TNC expression. Taken together, these findings indicate that the regulatory landscape within a cell is very stable but, by combining functional genomic tools gene-environmental interactions of clinical importance, can be detected and possibly used as biomarkers in future pharmacogenomic studies.

Breastfeeding provides many health benefits, but its impact on respiratory health remains unclear. This study addresses the complex and dynamic nature of the mother-milk-infant triad by investigating maternal genomic factors regulating human milk oligosaccharides (HMOs), and their associations with respiratory health among human milk-fed infants. Nineteen HMOs are quantified from 980 mothers of the CHILD Cohort Study. Genome-wide association studies identify HMO-associated loci on chromosome 19p13.3 and 19q13.33 (lowest P = 2.4e–118), spanning several fucosyltransferase (FUT) genes. We identify novel associations on chromosome 3q27.3 for 6′-sialyllactose (P = 2.2e–9) in the sialyltransferase (ST6GAL1) gene. These, plus additional associations on chromosomes 7q21.32, 7q31.32 and 13q33.3, are replicated in the independent INSPIRE Cohort. Moreover, gene-environment interaction analyses suggest that fucosylated HMOs may modulate overall risk of recurrent wheeze among preschoolers with variable genetic risk scores (P < 0.01). Thus, we report novel genetic factors associated with HMOs, some of which may protect the respiratory health of children.

The human milk microbiota (HMM) is thought to influence the long-term health of offspring. However, its role in asthma and atopy and the impact of host genomics on HMM composition remain unclear. Through the CHILD Cohort Study, we followed 885 pregnant mothers and their offspring from birth to 5 years and determined that HMM was associated with maternal genomics and prevalence of childhood asthma and allergic sensitization (atopy) among human milk-fed infants. Network analysis identified modules of correlated microbes in human milk that were associated with subsequent asthma and atopy in preschool-aged children. Moreover, reduced alpha-diversity and increased Lawsonella abundance in HMM were associated with increased prevalence of childhood atopy. Genome-wide association studies (GWASs) identified maternal genetic loci (e.g., ADAMTS8, NPR1, and COTL1) associated with HMM implicated with asthma and atopy, notably Lawsonella and alpha-diversity. Thus, our study elucidates the role of host genomics on the HMM and its potential impact on childhood asthma and atopy.

Gut microbiota has been associated with health and susceptibility to childhood diseases, including asthma and allergies. However, the genomic factors contributing to inter-individual variations in gut microbiota remain poorly understood. Our study integrates host genomics with early-life exposures to investigate main and interaction effects on gut microbiota during the first year of life. In addition, we identified gut microbes associated with childhood respiratory (asthma, wheeze) and atopic (atopic dermatitis, food/inhalant sensitization) outcomes. We leveraged microbiome data from infant stool at ages 3 months (N=779) and 1 year (N=770) from the CHILD Cohort Study. We identified microbial taxa and co-occurring network clusters associated with asthma and atopy by age 5 years. Genome-wide association studies and gene-by-environment interaction analyses determined main and interaction effects of host genomics and early-life environmental exposures (e.g., feeding practices, household pets, birth characteristics) on gut microbial features. Shifts in microbial taxa and network clusters during the first year of life were associated with childhood respiratory and atopic outcomes (P<0.05), some of which were sex-specific. Additionally, some of these implicated microbes were associated with host genomics and early-life exposures. For example, Blautia obeum was associated with reduced food/inhalant sensitization and genetic variants near the MARCO gene (P=9.4E-11). Also, variants in the SMAD2 gene interact with breastfeeding to influence the green microbial network cluster (P=8.3E-10), associated with asthma. Our study reports main and interaction effects of genomics and exposures on early-life gut microbiota, which may contribute to childhood asthma and atopy. Improved understanding of the factors contributing to gut dysbiosis will inform on early-life biomarkers and interventions.

Background: The role of epigenetic ageing in the environmental pathogenesis and prognosis of fibrotic interstitial lung disease (fILD) is unclear. We evaluated whether ambient particulate matter with diameter ≤2.5 μm (PM_2.5) and neighbourhood disadvantage exposures are associated with accelerated epigenetic ageing, and whether epigenetic age is associated with adverse clinical outcomes in patients with fILD.Methods: This multicentre, international, cohort study included patients with fILD from the University of Pittsburgh (UPitt, n=306) and University of British Columbia (UBC, n=170). 5-year PM_2.5exposures were estimated using satellite-derived hybrid models. Neighbourhood disadvantage was calculated using US and Canadian census-based metrics. Epigenetic age difference (EAD=epigenetic age−chronological age) was calculated using GrimAge analysis of blood DNA methylation data. Linear models assessed associations of exposures with EAD. Cox models assessed associations of EAD with transplant-free survival. Causal mediation analysis evaluated EAD mediation of exposure–survival relationships.Results: Median epigenetic age was 11.7 years older than chronological age in patients with fILD. In combined cohort analysis, each interquartile range (IQR) increase in PM_2.5was associated with 2.88 years (95% CI 1.39–4.38; p<0.001) increased EAD. In UPitt, each IQR neighbourhood disadvantage increase was associated with 1.16 years (95% CI 0.22–2.09; p=0.02) increased EAD. Increased EAD was associated with worse transplant-free survival (hazard ratio 1.17 per 1-year increase in EAD, 95% CI 1.10–1.24; p<0.001), with EAD mediating 40% of the PM_2.5–survival relationship and 59% of the neighbourhood disadvantage–survival relationship. Epigenetic age was also more strongly associated with transplant-free survival than chronological age.Conclusions: Epigenetic age acceleration is associated with worse survival and mediates adverse exposure impacts in fILD.

Background: A major impediment in the treatment of ovarian cancer is the relapse of chemotherapy-resistant tumors, which occurs in approximately 25% of patients. A better understanding of the biological mechanisms underlying chemotherapy resistance will improve treatment efficacy through genetic testing and novel therapies. Methods: Using data from high-grade serous ovarian carcinoma (HGSOC) patients in the Cancer Genome Atlas (TCGA), we classified those who remained progression-free for 12 months following platinum-taxane combination chemotherapy as “chemo-sensitive” (N = 160) and those who had recurrence within 6 months as “chemo-resistant” (N = 110). Univariate and multivariate analysis of expression microarray data were used to identify differentially expressed genes and co-expression gene networks associated with chemotherapy response. Moreover, we integrated genomics data to determine expression quantitative trait loci (eQTL). Results: Differential expression of the Valosin-containing protein (VCP) gene and five co-expression gene networks were significantly associated with chemotherapy response in HGSOC. VCP and the most significant co-expression network module contribute to protein processing in the endoplasmic reticulum, which has been implicated in chemotherapy response. Both univariate and multivariate analysis findings were successfully replicated in an independent ovarian cancer cohort. Furthermore, we identified 192 cis-eQTLs associated with the expression of network genes and 4 cis-eQTLs associated with BRCA2 expression. Conclusion: This study implicates both known and novel genes as well as biological processes underlying response to platinum-taxane-based chemotherapy among HGSOC patients.