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Asthma is the most common chronic condition in children and the third leading cause of hospitalization in pediatrics. The genome-wide association study catalog reports 140 studies with genome-wide significance. A polygenic risk score (PRS) with predictive value across ancestries has not been evaluated for this important trait.This study aimed to train and validate a PRS relying on genetic determinants for asthma to provide predictions for disease occurrence in pediatric cohorts of diverse ancestries.This study applied a Bayesian regression framework method using the Trans-National Asthma Genetic Consortium genome-wide association study summary statistics to derive a multiancestral PRS score, used one Electronic Medical Records and Genomics (eMERGE) cohort as a training set, used a second independent eMERGE cohort to validate the score, and used the UK Biobank data to replicate the findings. A phenome-wide association study was performed using the PRS to identify shared genetic etiology with other phenotypes.The multiancestral asthma PRS was associated with asthma in the 2 pediatric validation datasets. Overall, the multiancestral asthma PRS has an area under the curve (AUC) of 0.70 (95% CI, 0.69-0.72) in the pediatric validation 1 and AUC of 0.66 (0.65-0.66) in the pediatric validation 2 datasets. We found significant discrimination across pediatric subcohorts of European (AUC, 95% CI, 0.60 and 0.66), African (AUC, 95% CI, 0.61 and 0.66), admixed American (AUC, 0.64 and 0.70), Southeast Asian (AUC, 0.65), and East Asian (AUC, 0.73) ancestry. Pediatric participants with the top 5% PRS had 2.80 to 5.82 increased odds of asthma compared to the bottom 5% across the training, validation 1, and validation 2 cohorts when adjusted for ancestry. Phenome-wide association study analysis confirmed the strong association of the identified PRS with asthma (odds ratio, 2.71, PsubFDR/sub = 3.71 × 10sup-65/sup) and related phenotypes.A multiancestral PRS for asthma based on Bayesian posterior genomic effect sizes identifies increased odds of pediatric asthma.

BACKGROUND: Eosinophilic esophagitis (EoE) is an emerging, chronic, rare allergic disease associated with marked eosinophil accumulation in the esophagus. Prior genome-wide association studies (GWAS) have provided strong evidence for three genome-wide susceptibility loci. OBJECTIVE: We aimed to replicate known and suggestive EoE genetic risk loci and conduct a meta-analysis of previously reported datasets. METHODS: An EoE-Custom SNP Chip (EoE-CSC) containing 956 candidate EoE risk single-nucleotide polymorphisms (SNPs) was employed to genotype 627 cases and 365 controls. Statistical power was enhanced by adding 1990 external controls and performing meta-analyses with two independent EoE GWAS. RESULTS: Meta-analysis identified replicated association and genome-wide significance at six loci: 2p23 (two independent genetic effects), 5q22, 10p14, 11q13, and 16p13. Seven additional loci were identified at suggestive significance (p < 10(−6)): 1q31, 5q23, 6q15, 6q21, 8p21, 17q12, and 22q13. From these risk loci, 13 protein-coding EoE candidate risk genes were expressed in a genotype-dependent manner. EoE risk genes were expressed in disease-relevant cell types, including esophageal epithelia, fibroblasts, and immune cells, with some expressed as a function of disease activity. The genetic risk burden of EoE-associated genetic variants was markedly larger in cases relative to controls (P

The interplay between environmental and genetic factors plays a key role in the development of many autoimmune diseases. In particular, the Epstein-Barr virus (EBV) is an established contributor to multiple sclerosis, lupus, and other disorders. Previously, we demonstrated that the EBV nuclear antigen 2 (EBNA2) transactivating protein occupies up to half of the risk loci for a set of seven autoimmune disorders. To further examine the mechanistic roles played by EBNA2 at these loci on a genome-wide scale, we globally examined gene expression, chromatin accessibility, chromatin looping, and EBNA2 binding, in a B cell line that was 1) uninfected, 2) infected with a strain of EBV lacking EBNA2, or 3) infected with a strain that expresses EBNA2. We identified >400 EBNA2-dependent differentially expressed human genes and >5,000 EBNA2 binding events in the human genome. ATAC-seq analysis revealed >2,000 regions in the human genome with EBNA2-dependent chromatin accessibility, and HiChIP-seq data revealed >1,700 regions where EBNA2 altered chromatin looping interactions. Importantly, autoimmune genetic risk loci were highly enriched at the sites of these EBNA2-dependent chromatin-altering events. We present examples of autoimmune risk genotype-dependent EBNA2 events, nominating genetic risk mechanisms for autoimmune risk loci such as ZMIZ1. Taken together, our results reveal important interactions between host genetic variation and EBNA2-driven disease mechanisms. Further, our study highlights a critical role for EBNA2 in rewiring human gene regulatory programs through rearrangement of the chromatin landscape and nominates these interactions as components of genetic mechanisms that influence the risk of multiple autoimmune diseases.

The interplay between environmental and genetic factors plays a key role in the development of many autoimmune diseases. In particular, the Epstein–Barr virus (EBV) is an established contributor to multiple sclerosis, lupus, and other disorders. Previously, we showed that the EBV nuclear antigen 2 (EBNA2) transactivating protein occupies up to half of the risk loci for a set of seven autoimmune disorders. To further examine the mechanistic roles played by EBNA2 at these loci on a genome-wide scale, we globally examined gene expression, chromatin accessibility, chromatin looping, and EBNA2 binding in a B cell line that was (1) uninfected, (2) infected with a strain of EBV lacking EBNA2, or (3) infected with a strain that expresses EBNA2. We identified more than 400 EBNA2-dependent differentially expressed human genes and more than 5000 EBNA2 binding events in the human genome. ATAC-seq analysis revealed more than 2000 regions in the human genome with EBNA2-dependent chromatin accessibility, and HiChIP data revealed more than 1700 regions where EBNA2 altered chromatin looping interactions. Autoimmune genetic risk loci were highly enriched at the sites of these EBNA2-dependent chromatin-altering events. We present examples of autoimmune risk genotype–dependent EBNA2 events, nominating genetic risk mechanisms for autoimmune risk loci such as ZMIZ1. Taken together, our results reveal important interactions between host genetic variation and EBNA2-driven disease mechanisms. Further, our study highlights a critical role for EBNA2 in rewiring human gene regulatory programs through rearrangement of the chromatin landscape and nominates these interactions as components of genetic mechanisms that influence the risk of multiple autoimmune diseases.

Two screening protocols based on recursive partitioning and computational ligand docking methodologies, respectively, were employed for virtual screens of a compound library with 345,000 entries for novel inhibitors of the enzyme sarco/endoplasmic reticulum calcium ATPase (SERCA), a potential target for cancer chemotherapy. A total of 72 compounds that were predicted to be potential inhibitors of SERCA were tested in bioassays and 17 displayed inhibitory potencies at concentrations below 100 µM. The majority of these inhibitors were composed of two phenyl rings tethered to each other by a short link of one to three atoms. Putative interactions between SERCA and the inhibitors were identified by inspection of docking-predicted poses and some of the structural features required for effective SERCA inhibition were determined by analysis of the classification pattern employed by the recursive partitioning models.

Inhibitors of the transmembrane protein sarco/endoplasmic reticulum calcium ATPase (SERCA) are invaluable tools for the study of the enzyme’s physiological functions and they have been recognized as a promising new class of anticancer agents. For the discovery of novel enzyme inhibitors, small molecule docking for virtual screens of large compound libraries has become increasingly important. Since the performance of various docking routines varies considerably, depending on the target and the chemical nature of the ligand, we critically evaluated the performance of four frequently used programs – GOLD, AutoDock, Surflex-Dock, and FRED – for the docking of SERCA inhibitors based on the structures of thapsigargin, di-tert-butylhydroquinone, and cyclopiazonic acid. Evaluation criteria were docking accuracy using crystal structures as references, docking reproducibility, and correlation between docking scores and known bioactivities. The best overall results were obtained by GOLD and FRED. Docking runs with conformationally flexible binding sites produced no significant improvement of the results.

A public compound library with 260,000 compounds was screened virtually by computational docking for novel inhibitors of the transmembrane enzyme sarco/endoplasmic reticulum calcium ATPase (SERCA). Docking was performed with the program GOLD in conjunction with a high resolution X-ray crystal structure of SERCA. Compounds that were predicted to be active were tested in bioassays. Nineteen novel compounds were discovered that were capable of inhibiting the ATP hydrolysis activity of SERCA at concentrations below 50 μM. Crucial enzyme/inhibitor interactions were identified by analyzing the docking-predicted binding poses of active compounds. Like other SERCA inhibitors, the newly discovered compounds are of considerable medicinal interest because of their potential for cancer chemotherapy.

The ion transport activity of the sarco/endoplasmic reticulum calcium ATPase (SERCA) is specifically and potently inhibited by the small molecule 2,5-di-tert-butylhydroquinone (BHQ). In this study, we investigated the relative importance of the nature and position of BHQ's four substituents for enzyme inhibition by employing a combination of experimental and computational techniques. The inhibitory potencies of 21 commercially available or synthesized BHQ derivatives were determined in ATPase activity assays, and 11 compounds were found to be active. Maximum inhibitory potency was observed in compounds with two para hydroxyl groups, whereas BHQ analogues with only one hydroxyl group were still active, albeit with a reduced potency. The results also demonstrated that two alkyl groups were an absolute requirement for activity, with the most potent compounds having 2,5-substituents with four or five carbon atoms at each position. Using the program GOLD in conjunction with the ChemScore scoring function, the structures of the BHQ analogues were docked into the crystal structure of SERCA mimicking the enzyme's E(2) conformation. Analysis of the docking results indicated that inhibitor binding to SERCA was primarily mediated by a hydrogen bond between a hydroxyl group and Asp-59 and by hydrophobic interactions involving the bulky inhibitor alkyl groups. Attempts to dock BHQ into crystal structures corresponding to the E(1) conformation of the enzyme failed, because the conformational changes accompanying the E(2)/E(1) transition severely restricted the size of the binding site, suggesting that BHQ stabilizes the enzyme in its E(2) form. The potential role of Glu309 in enzyme inhibition is discussed in the context of the computational results. The docking scores correlated reasonably well with the measured inhibitory potencies and allowed the distinction between active and inactive compounds, which is a key requirement for future virtual screening of large compound databases for novel SERCA inhibitors.

Immunotherapy by cocaine-binding monoclonal antibodies (mAbs) has emerged as a promising strategy for the treatment of cocaine addiction. The human (gamma1 heavy chain)/murine (lambda light chain) chimeric mAb 2E2 has excellent affinity and specificity for cocaine and recent animal studies have demonstrated 2E2's ability in vivo to reduce cocaine levels in the brain as well as alter cocaine self-administration behavior in rats. In this study, we used mAb 2E2 amino acid sequence information to create a homology model for the 3-D structure of its Fv fragment. Subsequent computational docking studies revealed the intermolecular interactions potentially responsible for mAb 2E2's cocaine binding properties. The driving force of cocaine binding was identified as a combination of hydrophobic interactions and a single hydrogen bond between a light chain tyrosine residue and a carbonyl oxygen atom of cocaine. The model also allowed for an in silico evaluation of single/double residue mutations in the heavy and light chain variable regions that might further enhance mAb 2E2's cocaine binding properties.