The present study provides the first empirical evidence linking the larger social environment (SES) to T cell gene expression in the context of a clinical inflammatory disease. Among children with asthma, those from a low SES background showed overexpression of genes regulating a variety of inflammatory processes, including chemokine activity, stress responses and wound responses. Promoter based bioinformatics analyses identified transcription control pathways that may structure the observed patterns of differential gene expression, including decreased CREB, AP1 and NF-Y, and increased NFκB signalling. Children in the low SES group also reported poorer clinical outcomes, such as greater asthma symptoms. Although the cross sectional nature of this study precludes definitive conclusions about causal direction, the findings are consistent with the hypothesis that the larger social environment can get “under the skin” at the level of genomic transcription control pathways.
Genes overexpressed in children in the low SES group included: chemokine ligands such as CXCL4 and CXCL7 which recruit and activate leucocytes;23
those involved in antigen processing and presentation (MHC class II protein complexes), a key feature in asthma inflammatory biology; those related to oxidative stress (SOD2
), which recruits and activates immune cells, prolonging inflammation; and those related to calcium binding proteins (S100A8
), which have chemotactic effects on leucocytes and proinflammatory effects on endothelial cells.24 25
These patterns suggest molecular regulatory mechanisms that may heighten inflammation and worsen clinical outcomes in children with asthma from a low SES background.
Genes overexpressed in children in the high SES group included: those encoding heat shock proteins (HSPA1A
), which protect cells from inflammatory molecules such as reactive oxygen species, and are protective against pulmonary inflammation26 27
; those involved in cell differentiation and proliferation, such as c-fos and c-jun, which are increased in response to exposure to reactive oxygen species28
; those related to cell cycle control (BTG2
), which helps contain the effects of DNA damage29
; and those involved in the methylation, or silencing, of genes. Note that FOS
gene products also encode key components of the AP1 family of transcription factors, which in promoter based bioinformatic analyses showed increased activity in the high SES group. Taken together, these patterns suggest that among children with asthma from a high SES background, heightened inflammation may be counterbalanced by cellular regulatory mechanisms aimed at containing the damage due to inflammation.
This study also identified candidate transcription control pathways that may orchestrate differential patterns of gene expression as a function of SES. Bioinformatic analyses indicated downregulated activity of CREB, AP1 and NF-Y, and upregulated NFκB mediated transcription in children with asthma from a low SES background. CREB mediates transcriptional responses to β adrenergic receptor signalling through the adenylyl cyclase/cAMP/protein kinase A pathway.22 30
Adenylyl cyclase activity is impaired after allergen challenge in patients with asthma.31
Diminished regulatory signalling from cAMP pathways could lead to increased activation of T cells, and subsequent expression of Th-2 cytokines.31
Reduced CREB signalling may also decrease the efficacy of bronchodilators used as therapeutic agents in asthma. These patterns are consistent with decreased β adrenergic receptor mRNA found in lymphocytes of children with asthma with chronic and acute life stress.14
Bioinformatic analyses also indicated reduced NF-Y mediated transcription in children with asthma from a low SES background. Like CREB, NF-Y is phosphorylated by PKA, and may thus serve as an indicator of signalling along the β adrenergic signalling pathway.32
The fact that both transcription factors showed downregulation in the low SES group suggests multiple parallel deficiencies across catecholamine signalling pathways.
Bioinformatic analyses also indicated upregulated NFκB signalling in children with asthma in the low SES group. NFκB transactivates a wide variety of inflammatory mediators. Some data suggest that elevated cAMP activity can inhibit NFκB activity33
; hence increased NFκB and decreased CREB signalling could represent a common regulatory alteration that shifts gene expression profiles towards a more inflammatory phenotype in children from low SES backgrounds.
Our findings are consistent with previous research that has investigated functional immune measures. For example, children with asthma from a low SES background show greater production of Th-2 cytokines and greater eosinophil counts compared with those from a high SES background.12
Greater stress has been linked to in vivo inflammatory responses to allergen challenge and in vitro cytokine production in patients with asthma13 34
and predisposed to allergic disease.35
Furthermore, stress has been linked to reduced expression of genes coding for hormonal receptors that regulate inflammation.14
Statistical analyses revealed that interpretations of stress accounts for some of the SES related differences in indicators of CREB and NFκB activity. This suggests that in order for the social environment to have biological effects, it may have to first be perceived in a threatening manner. In turn, these cognitive perceptions may come with biological costs in transcriptional regulation and inflammatory biology. We note there could be numerous other pathways linking SES to genomic patterns, which should be tested in future studies.
It is unclear whether similar effects would be found in healthy children. However, even if similar effects were evident, these biological mechanisms could still have different implications for those with a pre-existing inflammatory disease. Nonetheless, it would be important for future research to test the effects of SES on gene expression profiles in healthy individuals as well.
Limitations include the observational design, precluding conclusions about causality and directionality. This is a necessary limitation to human work involving social factors that are difficult to randomly assign (eg, socioeconomic status). Secondly, the sample size is small by epidemiological standards, although not unusual for genome-wide microarray studies. One concern about small samples is insufficient power; however, the significant differences in several transcription control pathways suggest that the magnitude of effects is large enough to be detected in a sample of this size. A second concern is whether the findings will be robust and reliable. However, note that the bioinformatics approach used in this study capitalises on the data from thousands of genes to form aggregate and more reliable indicators of transcription factor activity. Thirdly, microarray technology is sometimes criticised as being too exploratory. In this study, however, microarray data were used to test an a priori hypothesis of SES increases in inflammation due to specific hormonal signalling pathways documented in previous research.12 14
Furthermore, the use of false discovery rate analysis is a standard approach in the genomic literature for adjusting statistics to account for multiple comparisons. Nevertheless, replicating these results in other samples would be important in future studies. Finally, selection of the CD2 antigen to isolate T lymphocytes may have permitted contamination by natural killer (NK) cells. (CD3 markers were not used because the immunomagnetic separation process for CD3 would have activated T cells.) However, the present results were not significantly altered in analyses controlling for NK cell marker mRNA.
The present data identified a distinct transcriptional finger-print of low SES environments, and candidate transcription control pathways structuring those differences, in T lymphocytes from children with asthma. Children with asthma from a low SES background showed overexpression of genes related to inflammation, chemokine activity, and stress and wound responses, and bioinformatics indications of reduced CREB, AP1 and NF-Y, and increased NFκB signalling. This study provides the first clinical evidence in asthma that broader social environments affect processes at the genomic level, specifically in terms of transcription control pathways that regulate inflammation and catecholamine signalling. Because these pathways are the primary targets of many asthma medications, these findings suggest that the larger social environment may also affect the efficacy of asthma therapeutics. Finally, perceptions of stress play an important role in explaining how SES gets transduced into alterations at the genomic level. Overall, these findings provide new insights into the mechanisms by which social factors affect the course of inflammatory diseases, and highlight the need for future research investigating how the pathophysiology of asthma is shaped by social environments.