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Cigarette smoke (CS) facilitates adverse effects on the airway inflammation and treatment of asthma. Here, we investigated the mechanisms by which CS exacerbates asthma. The roles of IL-33 and IL-35 in asthma development were examined by treatment with IL-33 knockout (IL-33 KO) or transfection of adenovirus encoding IL-35 (Ad-IL-35) in a murine model of cigarette smoke-exposure asthma. Furthermore, the involvement of IL-33 and IL-35 in regulating DCs and Th2/Th17 cells was examined in a coculture system of DCs with CD4+ T cells. Additionally, we observed the effect of CpG-ODNs on the balance of IL-33 and IL-35. We show that CS and house dust mite (HDM) exposure induced IL-33 and suppressed IL-35 levels in cigarette smoke-exposure asthma in vivo and in vitro. Treatment with IL-33 KO or Ad-IL-35 significantly attenuated airway hyperreactivity, goblet hyperplasia, airway remodelling, and eosinophil and neutrophil infiltration in the lung tissues from asthmatic mice. Furthermore, we demonstrated reciprocal regulation between CS and HDM-modulated IL-33 and IL-35. Mechanistically, IL-33 KO (or anti-ST2) and Ad-IL-35 attenuated Th2- and Th17-associated inflammation by downregulating TSLP-DC signalling. Finally, administration of CpG-ODNs suppressed the expression of IL-33/ST2 and elevated the levels of IL-35, which is mainly derived from CD4+Foxp+ Tregs, to alleviate Th2- and Th17-associated inflammation by inhibiting the activation of BMDCs. Taken together, the IL-33/ST2 pathway drives the DC-Th2 and Th17 responses of cigarette smoke-exposure asthma, while IL-35 has the opposite effect. CpG-ODNs represent a potential therapeutic strategy for modulating the balance of IL-33 and IL-35 to suppress allergic airway inflammation. [ABSTRACT FROM AUTHOR]

Smoking has caused great public health burdens in the global. Although socioeconomic factors have been confirmed to substantially influence smoking behaviors, the impact of comprehensive social deprivations on smoking behavior and related biological mechanisms are still unclear. Supported by UK Biobank cohort, we randomly divided 369,915 participants into discovery cohort (60%) and replication cohort (40%). We first tested the associations for index of multiple deprivation (IMD) and 7 IMD subdomains with ever-smoking and daily smoking frequency using regression models in both cohorts. Genome-wide by environment interaction study (GWEIS) was further conducted by using PLINK2.0 to detect the effects of the interactions between SNPs and IMD subdomains on two smoking behaviors. In discovery and replication cohorts, we observed the more deprivation status the individuals were in, the higher daily smoking frequency or risk to be ever smokers. And among the subdomains of IMD, income, education, health, living environment, and crime deprivation were positively associated with the risk of smoking behaviors, while employment deprivation was negatively correlated with smoking behaviors (all P < 0.0125). Totally, GWEIS analysis detected 23 shared significant socioeconomic-deprivation interacted loci for daily smoking frequency in two cohorts, such as rs116680599 at 2p16.3 (NRXN1, Pdiscovery = 7.68 × 10−14, Preplication = 1.96 × 10−2) and rs150451424 at 16p13.3 (RBFOX1, Pdiscovery = 1.89 × 10−10, Preplication = 1.96 × 10−2) interacting with employment deprivation. We illustrated the diverse effects of IMD on smoking behaviors and provided insights for the biological mechanisms of the interaction effects between socioeconomic deprivation with genetic factors on smoking behaviors. [ABSTRACT FROM AUTHOR]

Immune dysregulation has been widely observed in patients with psychiatric disorders. This study aims to examine the association between HLA alleles and depression and anxiety. Using data from the UK Biobank, we performed regression analyses to assess the association of 359 HLA alleles with depression and anxiety, as determined by Patient Health Questionnaire (PHQ) score (n = 120,033), self‐reported depression (n = 121,685), general anxiety disorder (GAD‐7) score (n = 120,590), and self‐reported anxiety (n = 108,310). Subsequently, we conducted gene environmental interaction study (GEIS) to evaluate the potential effects of interactions between HLA alleles and environmental factors on the risk of depression and anxiety. Sex stratification was implemented in all analysis. Our study identified two significant HLA alleles associated with self‐reported depression, including HLA‐C*07:01 (β = −0.015, p = 5.54 × 10−5) and HLA‐B*08:01 (β = −0.015, p = 7.78 × 10−5). Additionally, we identified four significant HLA alleles associated with anxiety score, such as HLA‐DRB1*07:01 (β = 0.084, p = 9.28 × 10−5) and HLA‐B*57:01 (β = 0.139, p = 1.22 × 10−4). GEIS revealed that certain HLA alleles interacted with environmental factors to influence mental health outcomes. For instance, HLA‐A*02:07 × cigarette smoking was associated with depression score (β = 0.976, p = 1.88 × 10−6). Moreover, sex stratification analysis revealed significant sex‐based differences in the interaction effects of certain HLA alleles with environmental factors. Our findings indicate the considerable impact of HLA alleles on the risks of depression and anxiety, providing valuable insights into the functional relevance of immune dysfunction in these conditions. [ABSTRACT FROM AUTHOR]

Smoking and alcohol consumption were associated with the development of depression and anxiety. 3′UTR APA quantitative trait loci (3'aQTLs) have been associated with multiple health states and conditions. Our aim is to evaluate the interactive effects of 3'aQTLs-alcohol consumption/tobacco smoking on the risk of anxiety and depression. The 3'aQTL data of 13 brain regions were extracted from the large-scale 3'aQTL atlas. The phenotype data (frequency of cigarette smoking and alcohol drinking, anxiety score, self-reported anxiety, depression score and self-reported depression) of 90,399–103,011 adults aged 40–69 years living in the UK and contributing to the UK Biobank during 2006–2010, were obtained from the UK Biobank cohort. The frequency of cigarette smoking and alcohol drinking of each subject were defined by the amount of smoking and alcohol drinking of self-reported, respectively. The continuous alcohol consumption/smoking terms were further categorized in tertiles. 3'aQTL-by-environmental interaction analysis was then performed to evaluate the associations of gene-smoking/alcohol consumption interactions with anxiety and depression using generalized linear model (GLM) of PLINK 2.0 with an additive mode of inheritance. Furthermore, GLM was also used to explore the relationship between alcohol consumption/smoking with hazard of anxiety/depression stratified by allele for the significant genotyped SNPs that modified the alcohol consumption/smoking-anxiety/depression association. The interaction analysis identified several candidate 3'aQTLs-alcohol consumption interactions, such as rs7602638 located in PPP3R1 (β = 0.08, P = 6.50 × 10−6) for anxiety score; rs10925518 located in RYR2 (OR = 0.95, P = 3.06 × 10−5) for self-reported depression. Interestingly, we also observed that the interactions between TMOD1 (β = 0.18, P = 3.30 × 10−8 for anxiety score; β = 0.17, P = 1.42 × 10−6 for depression score), ZNF407 (β = 0.17, P = 2.11 × 10−6 for anxiety score; β = 0.15, P = 4.26 × 10−5 for depression score) and alcohol consumption was not only associated with anxiety, but related to depression. Besides, we found that relationship between alcohol consumption and hazard of anxiety/depression was significantly different for different SNPs genotypes, such as rs34505550 in TMOD1 (AA: OR = 1.03, P = 1.79 × 10−6; AG: OR = 1.00, P = 0.94; GG: OR = 1.00, P = 0.21) for self-reported anxiety. The identified 3'aQTLs-alcohol consumption/smoking interactions were associated with depression and anxiety, and its potential biological mechanisms need to be further revealed. Our study identified important interactions between candidate 3'aQTL and alcohol consumption/smoking on depression and anxiety, and found that the 3'aQTL may modify the associations between consumption/smoking with depression and anxiety. These findings may help to further explore the pathogenesis of depression and anxiety. • Interaction between rs7602638 located in PPP3R1 and alcohol consumption was positively associated with anxiety score. • Interaction between rs10925518 in RYR2 and alcohol consumption was negatively correlated with self-reported depression. • Interactions between TMOD1, NLRP1, ZNF407 and alcohol consumption were positively associated with anxiety and depression. [ABSTRACT FROM AUTHOR]