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Differential DNA methylation associated with allergy might provide novel insights into the shared or unique etiology of asthma, rhinitis, and eczema. We sought to identify DNA methylation profiles associated with childhood allergy. Within the European Mechanisms of the Development of Allergy (MeDALL) consortium, we performed an epigenome-wide association study of whole blood DNA methylation by using a cross-sectional design. Allergy was defined as having symptoms from at least 1 allergic disease (asthma, rhinitis, or eczema) and positive serum-specific IgE to common aeroallergens. The discovery study included 219 case patients and 417 controls at age 4 years and 228 case patients and 593 controls at age 8 years from 3 birth cohorts, with replication analyses in 325 case patients and 1111 controls. We performed additional analyses on 21 replicated sites in 785 case patients and 2124 controls by allergic symptoms only from 8 cohorts, 3 of which were not previously included in analyses. We identified 80 differentially methylated CpG sites that showed a 1% to 3% methylation difference in the discovery phase, of which 21 (including 5 novel CpG sites) passed genome-wide significance after meta-analysis. All 21 CpG sites were also significantly differentially methylated with allergic symptoms and shared between asthma, rhinitis, and eczema. The 21 CpG sites mapped to relevant genes, including ACOT7 , LMAN3, and CLDN23. All 21 CpG sties were differently methylated in asthma in isolated eosinophils, and 10 were replicated in respiratory epithelium. Reduced whole blood DNA methylation at 21 CpG sites was significantly associated with childhood allergy. The findings provide novel insights into the shared molecular mechanisms underlying asthma, rhinitis, and eczema. [ABSTRACT FROM AUTHOR]

Epigenetic mechanisms, including methylation, can contribute to childhood asthma. Identifying DNA methylation profiles in asthmatic patients can inform disease pathogenesis. We sought to identify differential DNA methylation in newborns and children related to childhood asthma. Within the Pregnancy And Childhood Epigenetics consortium, we performed epigenome-wide meta-analyses of school-age asthma in relation to CpG methylation (Illumina450K) in blood measured either in newborns, in prospective analyses, or cross-sectionally in school-aged children. We also identified differentially methylated regions. In newborns (8 cohorts, 668 cases), 9 CpGs (and 35 regions) were differentially methylated (epigenome-wide significance, false discovery rate < 0.05) in relation to asthma development. In a cross-sectional meta-analysis of asthma and methylation in children (9 cohorts, 631 cases), we identified 179 CpGs (false discovery rate < 0.05) and 36 differentially methylated regions. In replication studies of methylation in other tissues, most of the 179 CpGs discovered in blood replicated, despite smaller sample sizes, in studies of nasal respiratory epithelium or eosinophils. Pathway analyses highlighted enrichment for asthma-relevant immune processes and overlap in pathways enriched both in newborns and children. Gene expression correlated with methylation at most loci. Functional annotation supports a regulatory effect on gene expression at many asthma-associated CpGs. Several implicated genes are targets for approved or experimental drugs, including IL5RA and KCNH2. Novel loci differentially methylated in newborns represent potential biomarkers of risk of asthma by school age. Cross-sectional associations in children can reflect both risk for and effects of disease. Asthma-related differential methylation in blood in children was substantially replicated in eosinophils and respiratory epithelium. [ABSTRACT FROM AUTHOR]

Background Circulating levels of the chitinase-like protein YKL-40 are influenced by genetic variation in its encoding gene (chitinase 3–like 1 [CHI3L1] ) and are increased in patients with several diseases, including asthma. Epigenetic regulation of circulating YKL-40 early in life is unknown. Objective We sought to determine (1) whether methylation levels at CHI3L1 CpG sites mediate the association of CHI3L1 single nucleotide polymorphisms (SNPs) with YKL-40 levels in the blood and (2) whether these biomarkers ( CHI3L1 SNPs, methylation profiles, and YKL-40 levels) are associated with asthma in early childhood. Methods We used data from up to 2405 participants from the Spanish Infancia y Medio Ambiente; the Swedish Barn/Children, Allergy, Milieu, Stockholm, Epidemiological survey; and the Dutch Prevention and Incidence of Asthma and Mite Allergy birth cohorts. Associations between 68 CHI3L1 SNPs, methylation levels at 14 CHI3L1 CpG sites in whole-blood DNA, and circulating YKL-40 levels at 4 years of age were tested by using correlation analysis, multivariable regression, and mediation analysis. Each of these biomarkers was also tested for association with asthma at 4 years of age by using multivariable logistic regression. Results YKL-40 levels were significantly associated with 7 SNPs and with methylation at 5 CpG sites. Consistent associations between these 7 SNPs (particularly rs10399931 and rs4950928) and 5 CpG sites were observed. Alleles linked to lower YKL-40 levels were associated with higher methylation levels. Participants with high YKL-40 levels (defined as the highest YKL-40 tertile) had increased odds for asthma compared with subjects with low YKL-40 levels (meta-analyzed adjusted odds ratio, 1.90 [95% CI, 1.08-3.36]). In contrast, neither SNPs nor methylation levels at CpG sites in CHI3L1 were associated with asthma. Conclusions The effects of CHI3L1 genetic variation on circulating YKL-40 levels are partly mediated by methylation profiles. In our study YKL-40 levels, but not CHI3L1 SNPs or methylation levels, were associated with childhood asthma. [ABSTRACT FROM AUTHOR]

Bacillus Calmette-Guérin (BCG) vaccination is a prototype model for the study of trained immunity (TI) in humans, and results in a more effective response of innate immune cells upon stimulation with heterologous stimuli. Here, we investigate the heterogeneity of TI induction by single-cell RNA sequencing of immune cells collected from 156 samples. We observe that both monocytes and CD8+ T cells show heterologous transcriptional responses to lipopolysaccharide, with an active crosstalk between these two cell types. Furthermore, the interferon-γ pathway is crucial in BCG-induced TI, and it is upregulated in functional high responders. Data-driven analyses and functional experiments reveal STAT1 to be one of the important transcription factors for TI shared in all identified monocyte subpopulations. Finally, we report the role of type I interferon-related and neutrophil-related TI transcriptional programs in patients with sepsis. These findings provide comprehensive insights into the importance of monocyte heterogeneity during TI in humans. [Display omitted] • IFN-γ plays an important role in amplifying trained immunity response • Monocytes show heterogeneous trained immunity capacity after in vivo BCG vaccination • Trained monocytes are regulated by different transcription factors including STAT1 • A developed tool for user to test trained immunity signatures in transcriptome data Li et al. show that BCG vaccination induces an enhanced antimicrobial response upon secondary stimulation, and this effect is heterogeneous at single-cell level. These findings provide comprehensive insights into the molecular mechanism of trained immunity and its role in immune-mediated diseases. [ABSTRACT FROM AUTHOR]

Abstract: Purpose: Multivariate modeling of complications after radiotherapy is frequently used in conjunction with data driven variable selection. This study quantifies the risk of overfitting in a data driven modeling method using bootstrapping for data with typical clinical characteristics, and estimates the minimum amount of data needed to obtain models with relatively high predictive power. Materials and methods: To facilitate repeated modeling and cross-validation with independent datasets for the assessment of true predictive power, a method was developed to generate simulated data with statistical properties similar to real clinical data sets. Characteristics of three clinical data sets from radiotherapy treatment of head and neck cancer patients were used to simulate data with set sizes between 50 and 1000 patients. A logistic regression method using bootstrapping and forward variable selection was used for complication modeling, resulting for each simulated data set in a selected number of variables and an estimated predictive power. The true optimal number of variables and true predictive power were calculated using cross-validation with very large independent data sets. Results: For all simulated data set sizes the number of variables selected by the bootstrapping method was on average close to the true optimal number of variables, but showed considerable spread. Bootstrapping is more accurate in selecting the optimal number of variables than the AIC and BIC alternatives, but this did not translate into a significant difference of the true predictive power. The true predictive power asymptotically converged toward a maximum predictive power for large data sets, and the estimated predictive power converged toward the true predictive power. More than half of the potential predictive power is gained after approximately 200 samples. Our simulations demonstrated severe overfitting (a predicative power lower than that of predicting 50% probability) in a number of small data sets, in particular in data sets with a low number of events (median: 7, 95th percentile: 32). Recognizing overfitting from an inverted sign of the estimated model coefficients has a limited discriminative value. Conclusions: Despite considerable spread around the optimal number of selected variables, the bootstrapping method is efficient and accurate for sufficiently large data sets, and guards against overfitting for all simulated cases with the exception of some data sets with a particularly low number of events. An appropriate minimum data set size to obtain a model with high predictive power is approximately 200 patients and more than 32 events. With fewer data samples the true predictive power decreases rapidly, and for larger data set sizes the benefit levels off toward an asymptotic maximum predictive power. [Copyright &y& Elsevier]

Purpose: To investigate the applicability and value of double cross-validation and permutation tests as established statistical approaches in the validation of normal tissue complication probability (NTCP) models. Methods and Materials: A penalized regression method, LASSO (least absolute shrinkage and selection operator), was used to build NTCP models for xerostomia after radiation therapy treatment of head-and-neck cancer. Model assessment was based on the likelihood function and the area under the receiver operating characteristic curve. Results: Repeated double cross-validation showed the uncertainty and instability of the NTCP models and indicated that the statistical significance of model performance can be obtained by permutation testing. Conclusion: Repeated double cross-validation and permutation tests are recommended to validate NTCP models before clinical use. [ABSTRACT FROM AUTHOR]

Purpose: To study the impact of different statistical learning methods on the prediction performance of multivariate normal tissue complication probability (NTCP) models. Methods and Materials: In this study, three learning methods, stepwise selection, least absolute shrinkage and selection operator (LASSO), and Bayesian model averaging (BMA), were used to build NTCP models of xerostomia following radiotherapy treatment for head and neck cancer. Performance of each learning method was evaluated by a repeated cross-validation scheme in order to obtain a fair comparison among methods. Results: It was found that the LASSO and BMA methods produced models with significantly better predictive power than that of the stepwise selection method. Furthermore, the LASSO method yields an easily interpretable model as the stepwise method does, in contrast to the less intuitive BMA method. Conclusions: The commonly used stepwise selection method, which is simple to execute, may be insufficient for NTCP modeling. The LASSO method is recommended. [ABSTRACT FROM AUTHOR]

The Bacille Calmette-Guerin (BCG) vaccine is a well-established inducer of innate immune memory (also termed trained immunity), causing increased cytokine production upon heterologous secondary stimulation. Innate immune responses are known to be influenced by season, but whether seasons impact induction of trained immunity is not known. To explore the influence of season on innate immune memory induced by the BCG vaccine, we vaccinated healthy volunteers with BCG either during winter or spring. Three months later, we measured the ex vivo cytokine responses against heterologous stimuli, analyzed gene expressions and epigenetic signatures of the immune cells, and compared these with the baseline before vaccination. BCG vaccination during winter induced a stronger increase in the production of pro-inflammatory cytokines by peripheral blood mononuclear cells (PBMCs) upon stimulation with different bacterial and fungal stimuli, compared to BCG vaccination in spring. In contrast, winter BCG vaccination resulted in lower IFNγ release in PBMCs compared to spring BCG vaccination. Furthermore, NK cells of the winter-vaccinated people had a greater pro-inflammatory cytokine and IFNγ production capacity upon heterologous stimulation. BCG had only minor effects on the transcriptome of monocytes 3 months later. In contrast, we identified season-dependent epigenetic changes in monocytes and NK cells induced by vaccination, partly explaining the higher immune cell reactivity in the winter BCG vaccination group. These results suggest that BCG vaccination during winter is more prone to induce a robust trained immunity response by activating and reprogramming the immune cells, especially NK cells. (Dutch clinical trial registry no. NL58219.091.16) [ABSTRACT FROM AUTHOR]

The volatile chemical constituents in traditional Chinese medicine (TCM), Artemisia capillaris herba, were determined by gas chromatography–mass spectrometry (GC–MS). The acquired two-dimensional data were resolved by correlative chemometric resolution methods. The noise in the raw data is pretreated by roughness penalty smoothing method. With the data denoised, heteroscedastic noise and signal-to-noise ratio were decreased apparently, which was favorable to the determination of component number. The selective range can be extracted from rankmap obtained by fixed size moving window evolving factor analysis (FSMWEFA) conveniently. The overlapped chromatographic peaks were resolved into pure chromatograms and pure spectra with evolving window orthogonal projection (EWOP). The purity of the resolved pure spectra were improved furthermore with the heteroscedastic noise decreased through roughness penalty smoothing method, although the basic structure of the raw data changes little. Qualitative analysis was performed by similarity search in NIST147 and Willey library. Pure chromatograms are in favor of quantitative analysis, which was obtained by total volume integration. Forty-two of seventy-five separated constituents in essential oil, accounting for 89.03% of the total content, were identified. The result proves the combined approaches to be powerful for the analysis of complex herbal samples. [Copyright &y& Elsevier]

• Urate-primed PBMCs of hyperuricemic and gout patients show dysregulated cytokine production. • SOCS3 is enhanced in urate-primed myeloid cells, and this is conserved after a second stimulation with LPS. • pSTAT3 is downregulated by urate treatment in vitro, concomitant with reduction of IL-1Ra. • Urate-priming effect is not observed in patients with constitutively activated STAT3. Hyperuricaemia is necessary for gout. High urate concentrations have been linked to inflammation in mononuclear cells. Here, we explore the role of the suppressor of cytokine signaling 3 (SOCS3) in urate-induced inflammation. Peripheral blood mononuclear cells (PBMCs) from gout patients, hyperuricemic and normouricemic individuals were cultured for 24 h with varying concentrations of soluble urate, followed by 24 h restimulation with lipopolysaccharides (LPS) ± monosodium urate (MSU) crystals. Transcriptomic profiling was performed using RNA-Sequencing. DNA methylation was assessed using Illumina Infinium® MethylationEPIC BeadChip system (EPIC array). Phosphorylation of signal transducer and activator of transcription 3 (STAT3) was determined by flow cytometry. Cytokine responses were also assessed in PBMCs from patients with JAK2 V617F tyrosine kinase mutation. PBMCs pre-treated with urate produced more interleukin-1beta (IL-1β) and interleukin-6 (IL-6) and less interleukin-1 receptor anatagonist (IL-1Ra) after LPS simulation. In vitro, urate treatment enhanced SOCS3 expression in control monocytes but no DNA methylation changes were observed at the SOCS3 gene. A dose-dependent reduction in phosphorylated STAT3 concomitant with a decrease in IL-1Ra was observed with increasing concentrations of urate. PBMCs with constitutively activated STAT3 (JAK2 V617F mutation) could not be primed by urate. In vitro, urate exposure increased SOCS3 expression, while urate priming, and subsequent stimulation resulted in decreased STAT3 phosphorylation and IL-1Ra production. There was no evidence that DNA methylation constitutes a regulatory mechanism of SOCS3. Elevated SOCS3 and reduced pSTAT3 could play a role in urate-induced hyperinflammation since urate priming had no effect in PBMCs from patients with constitutively activated STAT3. [ABSTRACT FROM AUTHOR]

Epigenetics functions as a bridge between host genetic & environmental factors, aiding in human health and diseases. Many immune-related diseases, including infectious and allergic diseases, have been linked to epigenetic mechanisms, particularly DNA methylation. In this review, we summarized an updated overview of DNA methylation and its importance in personalized medicine, and demonstrated that DNA methylation has excellent potential for disease prevention, diagnosis, and treatment in a personalized manner. The future implications and limitations of the DNA methylation study have also been well-discussed. [ABSTRACT FROM AUTHOR]

• PM 2.5 is associated with altered nasal DNA methylation even at low exposure levels. • Exposure duration is a key factor in identifying PM 2.5 and methylome associations. • PM 2.5 may alter methylation of cell cycle and innate immune genes. PM 2.5- induced adverse effects on respiratory health may be driven by epigenetic modifications in airway cells. The potential impact of exposure duration on epigenetic alterations in the airways is not yet known. We aimed to study associations of fine particulate matter PM 2.5 exposure with DNA methylation in nasal cells. We conducted nasal epigenome-wide association analyses within 503 children from Project Viva (mean age 12.9 y), and examined various exposure durations (1-day, 1-week, 1-month, 3-months and 1-year) prior to nasal sampling. We used residential addresses to estimate average daily PM 2.5 at 1 km resolution. We collected nasal swabs from the anterior nares and measured DNA methylation (DNAm) using the Illumina MethylationEPIC BeadChip. We tested 719,075 high quality autosomal CpGs using CpG-by-CpG and regional DNAm analyses controlling for multiple comparisons, and adjusted for maternal education, household smokers, child sex, race/ethnicity, BMI z-score, age, season at sample collection and cell-type heterogeneity. We further corrected for bias and genomic inflation. We tested for replication in a cohort from the Netherlands (PIAMA). In adjusted analyses, we found 362 CpGs associated with 1-year PM 2.5 (FDR < 0.05), 20 CpGs passing Bonferroni correction (P < 7.0x10-8) and 10 Differentially Methylated Regions (DMRs). In 445 PIAMA participants (mean age 16.3 years) 11 of 203 available CpGs replicated at P < 0.05. We observed differential DNAm at/near genes implicated in cell cycle, immune and inflammatory responses. There were no CpGs or regions associated with PM 2.5 levels at 1-day, 1-week, or 1-month prior to sample collection, although 2 CpGs were associated with past 3-month PM 2.5. We observed wide-spread DNAm variability associated with average past year PM 2.5 exposure but we did not detect associations with shorter-term exposure. Our results suggest that nasal DNAm marks reflect chronic air pollution exposure. [ABSTRACT FROM AUTHOR]