METHODS AND RESULTS: We investigated steady-state messenger RNA levels of 84 histone-modifying enzymes and related regulators in colony-stimulating factor-1 differentiated primary human macrophages using quantitative polymerase chain reaction. IFN-γ or IL-4 treatment for 6-48 h changed 11 mRNAs significantly. IFN-γ increased CIITA, KDM6B, and NCOA1, and IL-4 also increased KDM6B by 6 h. However, either cytokine decreased AURKB, ESCO2, SETD6, SUV39H1, and WHSC1, whereas IFN-γ alone decreased KAT2A, PRMT7, and SMYD3 mRNAs only after 18 h, which coincided with decreased cell proliferation. Rendering macrophages quiescent by growth factor starvation or adenovirus-mediated overexpression of p27(kip1) inhibited expression of AURKB, ESCO2, SUV39H1, and WHSC1, and mRNA levels were restored by overexpressing the S-phase transcription factor E2F1, implying their expression, at least partly, depended on proliferation. However, CIITA, KDM6B, NCOA1, KAT2A, PRMT7, SETD6, and SMYD3 were regulated independently of effects on proliferation. Silencing KDM6B, the only transcriptional activator upregulated by both IFN-γ and IL-4, pharmacologically or with short hairpin RNA, blunted a subset of responses to each cytokine.
CONCLUSION: These findings demonstrate that IFN-γ or IL-4 can regulate the expression of histone acetyl transferases and histone methyl transferases independently of effects on proliferation and that upregulation of the histone demethylase, KDM6B, assists phenotypic polarization by both cytokines.
Materials and Methods: The data were obtained from the Kuwait National Primary Immunodeficiency Disorders Registry during the period of 2004-2020.
Results: A total of 313 pediatric cases of IEI, 71% diagnosed at molecular level, were registered with a cumulative follow-up period of 29,734 months. Skin manifestations were seen in 40.3% of the patients, and they were among the presenting manifestations in 33%. Patients with skin manifestations were older at both onset and diagnosis ages of IEI symptoms, but this was statistically significant for the latter only. The diagnosis delay was significantly longer in patients with skin manifestations. There was a statistically significant association between having skin manifestations and IEI category, being more common in patients with complement deficiencies, combined immunodeficiencies, and diseases of immune dysregulation. There was no statistically significant association between having skin manifestations and both gender and survival. Skin infections were the most frequent manifestations followed by eczema and autoimmune associations. Among IEI with more than 10 cases, skin lesions were a consistent finding in dedicator of cytokinesis 8 (DOCK8) deficiency, hyper IgE syndrome, ataxia-telangiectasia, and recombination activation gene (RAG)1 deficiency.
Conclusions: Skin manifestations are common in IEI patients, and they had significant diagnosis delay and referral to specialists. Improvement of awareness about IEI is needed among pediatricians and dermatologists.
OBJECTIVE: The aim of this study was to identify the clinical features that affect age at diagnosis (AD) and time to the diagnosis of SCID.
METHODS: From 2005 to 2016, 147 SCID patients were referred to the Asian Primary Immunodeficiency Network. Patients with genetic diagnosis, age at presentation (AP), and AD were selected for study.
RESULTS: A total of 88 different SCID gene mutations were identified in 94 patients, including 49 IL2RG mutations, 12 RAG1 mutations, 8 RAG2 mutations, 7 JAK3 mutations, 4 DCLRE1C mutations, 4 IL7R mutations, 2 RFXANK mutations, and 2 ADA mutations. A total of 29 mutations were previously unreported. Eighty-three of the 94 patients fulfilled the selection criteria. Their median AD was 4 months, and the time to diagnosis was 2 months. The commonest SCID was X-linked (n = 57). A total of 29 patients had a positive FH. Candidiasis (n = 27) and bacillus Calmette-Guérin (BCG) vaccine infection (n = 19) were the commonest infections. The median age for candidiasis and BCG infection documented were 3 months and 4 months, respectively. The median absolute lymphocyte count (ALC) was 1.05 × 10(9)/L with over 88% patients below 3 × 10(9)/L. Positive FH was associated with earlier AP by 1 month (p = 0.002) and diagnosis by 2 months (p = 0.008), but not shorter time to diagnosis (p = 0.494). Candidiasis was associated with later AD by 2 months (p = 0.008) and longer time to diagnosis by 0.55 months (p = 0.003). BCG infections were not associated with age or time to diagnosis.
CONCLUSION: FH was useful to aid earlier diagnosis but was overlooked by clinicians and not by parents. Similarly, typical clinical features of SCID were not recognized by clinicians to shorten the time to diagnosis. We suggest that lymphocyte subset should be performed for any infant with one or more of the following four clinical features: FH, candidiasis, BCG infections, and ALC below 3 × 10(9)/L.
METHODS: Participants were recruited in Intensive Care Units (ICUs) from multiple UK hospitals, including fifty-nine patients with abdominal sepsis, eighty-four patients with pulmonary sepsis, forty-two SIRS patients with Out-of-Hospital Cardiac Arrest (OOHCA), sampled at four time points, in addition to thirty healthy control donors. Multiple clinical parameters were measured, including SOFA score, with many differences observed between SIRS and sepsis groups. Differential gene expression analyses were performed using microarray hybridization and data analyzed using a combination of parametric and non-parametric statistical tools.
RESULTS: Nineteen high-performance, differentially expressed mRNA biomarkers were identified between control and combined SIRS/Sepsis groups (FC>20.0, p<0.05), termed 'indicators of inflammation' (I°I), including CD177, FAM20A and OLAH. Best-performing minimal signatures e.g. FAM20A/OLAH showed good accuracy for determination of severe, systemic inflammation (AUC>0.99). Twenty entities, termed 'SIRS or Sepsis' (S°S) biomarkers, were differentially expressed between sepsis and SIRS (FC>2·0, p-value<0.05).
DISCUSSION: The best performing signature for discriminating sepsis from SIRS was CMTM5/CETP/PLA2G7/MIA/MPP3 (AUC=0.9758). The I°I and S°S signatures performed variably in other independent gene expression datasets, this may be due to technical variation in the study/assay platform.