Untargeted metabolomic profiling in children identifies novel pathways in asthma and atopy.

BACKGROUND: Asthma and other atopic disorders can present with varying clinical phenotypes marked by differential metabolomic manifestations and enriched biological pathways. OBJECTIVE: We sought to identify these unique metabolomic profiles in atopy and asthma. METHODS: We analyzed baseline nonfasted plasma samples from a large multisite pediatric population of 470 children aged <13 years from 3 different sites in the United States and France. Atopy positivity (At+) was defined as skin prick test result of ≥3 mm and/or specific IgE ≥ 0.35 IU/mL and/or total IgE ≥ 173 IU/mL. Asthma positivity (As+) was based on physician diagnosis. The cohort was divided into 4 groups of varying combinations of asthma and atopy, and 6 pairwise analyses were conducted to best assess the differential metabolomic profiles between groups. RESULTS: Two hundred ten children were classified as At-As-, 42 as At+As-, 74 as At-As+, and 144 as At+As+. Untargeted global metabolomic profiles were generated through ultra-high-performance liquid chromatography-tandem mass spectroscopy. We applied 2 independent machine learning classifiers and short-listed 362 metabolites as discriminant features. Our analysis showed the most diverse metabolomic profile in the At+As+/At-As- comparison, followed by the At-As+/At-As- comparison, indicating that asthma is the most discriminant condition associated with metabolomic changes. At+As+ metabolomic profiles were characterized by higher levels of bile acids, sphingolipids, and phospholipids, and lower levels of polyamine, tryptophan, and gamma-glutamyl amino acids. CONCLUSION: The At+As+ phenotype displays a distinct metabolomic profile suggesting underlying mechanisms such as modulation of host-pathogen and gut microbiota interactions, epigenetic changes in T-cell differentiation, and lower antioxidant properties of the airway epithelium.

Disease diagnostics using machine learning of immune receptors.

Clinical diagnosis typically incorporates physical examination, patient history, and various laboratory tests and imaging studies, but makes limited use of the human system's own record of antigen exposures encoded by receptors on B cells and T cells. We analyzed immune receptor datasets from 593 individuals to develop MAchine Learning for Immunological Diagnosis (Mal-ID) , an interpretive framework to screen for multiple illnesses simultaneously or precisely test for one condition. This approach detects specific infections, autoimmune disorders, vaccine responses, and disease severity differences. Human-interpretable features of the model recapitulate known immune responses to SARS-CoV-2, Influenza, and HIV, highlight antigen-specific receptors, and reveal distinct characteristics of Systemic Lupus Erythematosus and Type-1 Diabetes autoreactivity. This analysis framework has broad potential for scientific and clinical interpretation of human immune responses.

Combining avidin with CD63 improves basophil activation test accuracy in classifying peanut allergy.

BACKGROUND: Conventional basophil activation tests (BATs) measure basophil activation by the increased expression of CD63. Previously, fluorophore-labeled avidin, a positively-charged molecule, was found to bind to activated basophils, which tend to expose negatively charged granule constituents during degranulation. This study further compares avidin versus CD63 as basophil activation biomarkers in classifying peanut allergy. METHODS: Seventy subjects with either a peanut allergy (N = 47), a food allergy other than peanut (N = 6), or no food allergy (N = 17) were evaluated. We conducted BATs in response to seven peanut extract (PE) concentrations (0.01-10,000 ng/mL) and four control conditions (no stimulant, anti-IgE, fMLP (N-formylmethionine-leucyl-phenylalanine), and anti-FcεRI). We measured avidin binding and CD63 expression on basophils with flow cytometry. We evaluated logistic regression and XGBoost models for peanut allergy classification and feature identification. RESULTS: Avidin binding was correlated with CD63 expression. Both markers discriminated between subjects with and without a peanut allergy. Although small by percentage, an avidin+ /CD63- cell subset was found in all allergic subjects tested, indicating that the combination of avidin and CD63 could allow a more comprehensive identification of activated basophils. Indeed, we obtained the best classification accuracy (97.8% sensitivity, 96.7% specificity) by combining avidin and CD63 across seven PE doses. Similar accuracy was obtained by combining PE dose of 10,000 ng/mL for avidin and PE doses of 10 and 100 ng/mL for CD63. CONCLUSIONS: Avidin and CD63 are reliable BAT activation markers associated with degranulation. Their combination enhances the identification of activated basophils and improves the classification accuracy of peanut allergy.

Generation of LexA enhancer-trap lines in Drosophila by an international scholastic network.

Conditional gene regulation in Drosophila through binary expression systems like the LexA-LexAop system provides a superb tool for investigating gene and tissue function. To increase the availability of defined LexA enhancer trap insertions, we present molecular, genetic, and tissue expression studies of 301 novel Stan-X LexA enhancer traps derived from mobilization of the index SX4 line. This includes insertions into distinct loci on the X, II, and III chromosomes that were not previously associated with enhancer traps or targeted LexA constructs, an insertion into ptc, and seventeen insertions into natural transposons. A subset of enhancer traps was expressed in CNS neurons known to produce and secrete insulin, an essential regulator of growth, development, and metabolism. Fly lines described here were generated and characterized through studies by students and teachers in an international network of genetics classes at public, independent high schools, and universities serving a diversity of students, including those underrepresented in science. Thus, a unique partnership between secondary schools and university-based programs has produced and characterized novel resources in Drosophila, establishing instructional paradigms devoted to unscripted experimental science.

Prenatal trimester-specific intake of micronutrients: global DNA methylation and hydroxymethylation at birth and persistence in childhood.

The prenatal environment may program health and disease susceptibility via epigenetic mechanisms. We evaluated associations of maternal trimester-specific intake of micronutrients with global DNA methylation (%5mC) and 5-hydroxymethylation (%5hmC) at birth in cord blood and tested for persistence into childhood. We quantified global %5mC and %5hmC in cord blood cells (n = 434) and in leukocytes collected in early (n = 108) and mid-childhood (n = 390) from children in Project Viva, a pre-birth cohort from Boston, MA. Validated food frequency questionnaires estimated maternal first- and second-trimester intakes of vitamin B2, vitamin B6, vitamin B12, folate, betaine, choline, methionine, iron, and zinc. Mean (SD) cord blood %5mC and %5hmC was 5.62% (2.04) and 0.25% (0.15), respectively. Each µg increase in first-trimester B12 intake was associated with 0.002 lower %5hmC in cord blood (95% CI: -0.005, -0.0003), and this association persisted in early childhood (ß = -0.007; 95% CI: -0.01, -0.001) but not mid-childhood. Second-trimester iron (mg) was associated with 0.01 lower %5mC (95% CI: -0.02, -0.002) and 0.001 lower %5hmC (95% CI: -0.01, -0.00001) in cord blood only. Increased second-trimester zinc (mg) intake was associated with 0.003 greater %5hmC in early childhood (ß = 0.003; 95% CI: 0.0004, 0.006). Second-trimester folate was positively associated with %5hmC in early childhood only (ß = 0.08, 95% CI: 0.003, 0.16). Associations did not survive multiple testing adjustment; future replication is needed. Trimester-specific nutrients may impact various sensitive windows of epigenetic programming some with lasting effects in childhood. Further research is needed to understand the role of gene-specific epigenetic changes and how global DNA methylation measures relate to child health.

Immune imprinting, breadth of variant recognition, and germinal center response in human SARS-CoV-2 infection and vaccination.

During the SARS-CoV-2 pandemic, novel and traditional vaccine strategies have been deployed globally. We investigated whether antibodies stimulated by mRNA vaccination (BNT162b2), including third-dose boosting, differ from those generated by infection or adenoviral (ChAdOx1-S and Gam-COVID-Vac) or inactivated viral (BBIBP-CorV) vaccines. We analyzed human lymph nodes after infection or mRNA vaccination for correlates of serological differences. Antibody breadth against viral variants is lower after infection compared with all vaccines evaluated but improves over several months. Viral variant infection elicits variant-specific antibodies, but prior mRNA vaccination imprints serological responses toward Wuhan-Hu-1 rather than variant antigens. In contrast to disrupted germinal centers (GCs) in lymph nodes during infection, mRNA vaccination stimulates robust GCs containing vaccine mRNA and spike antigen up to 8 weeks postvaccination in some cases. SARS-CoV-2 antibody specificity, breadth, and maturation are affected by imprinting from exposure history and distinct histological and antigenic contexts in infection compared with vaccination.

Subduing the influence of PCR inhibitors on amplifying aged, degraded, and low copy number DNA: PCR enhancer cocktail-p and rescue PCR.

PCR inhibitors are a formidable problem to the study of aged, degraded, and/or low copy number DNA. As a result, there is a need to find alternate methods that ameliorate the efficacy of PCR. In this study, we attempted to use genetic methods to identify the species of salmonid (Oncorhynchus spp.) remains recovered from archaeological sites along the Feather River located in northern California, United States. In the process of doing so, we compared the efficacy of a PCR enhancer cocktail called "PEC-P" and a reagent rich PCR recipe called "rescue PCR" over standard PCR. Across all treatments (full concentration and 1:10 dilute eluates subjected to standard PCR, PEC-P, and rescue PCR) species identification was possible for 74 of 93 archaeological fish specimens (79.6%). Overall, six of the 93 samples (6.5%) consistently yielded species identification across all treatments. The species of ten specimens (10.8%) were uniquely identified from amplicons produced with either PEC-P or rescue PCR or both. Notably, the species of seven samples (7.5%) were uniquely identified with standard PCR over the alternative treatments. Considering both full concentration and 1:10 dilute eluates (N = 186), standard PCR performed as well as PEC-P (p = 0.1451) and rescue (p = 0.6753). Yet, considering results from full concentration eluates alone (N = 93), PEC-P (60.2%) outperformed both standard PCR (44.1%; p = 0.0277) and rescue PCR (40.9%; p = 0.0046). Stochasticity observed in our study cautions us against choosing a "best" performing method of those explored here and suggests their respective potentials to improve success may be sample dependent. When working with samples compromised by PCR inhibitors, it is useful to have alternative methodologies for subduing the problem. Both PEC-P and rescue PCR represent useful alternative methods for the study of aged, degraded, and/or low copy number DNA samples compromised by PCR inhibitors.