Evaluation of Analgesic Practice Changes Following the Nuss Procedure in Pediatric Patients.

INTRODUCTION: Pectus excavatum repair by the Nuss procedure results in severe postoperative pain. Regional blocks and intercostal nerve cryoablation (INC) have emerged as potential strategies to manage analgesia. This study compares pain-related outcomes following these perioperative interventions. METHODS: We reviewed charts of patients <18 y who underwent the Nuss procedure at Duke Children's Hospital from July 2018 to June 2022. Patients were divided into three groups by analgesic strategy: no block, regional catheters, or INC, representing the chronologic change in our practice. The primary outcome was total and daily in-hospital opioid utilization measured by oral morphine equivalents (OMEs). Secondary outcomes included average daily pain scores, length of stay, opioid refills after discharge, and complications. RESULTS: Twenty-one patients were included and analyzed: no block (n = 6), regional catheters (n = 7), and INC (n = 8). INC-treated patients required significantly lower total postoperative, in-hospital OMEs (64 ± 47 [mean ± standard deviation]) than those with no block (270 ± 217, P = 0.04) or those with regional catheters (273 ± 176, P = 0.03). INC was associated with longer average operative times (161 ± 36 min) than no block (105 ± 21 min, P = 0.005) or regional catheters (90 ± 11 min, P < 0.001). INC-treated patients had shorter hospital length of stays (median 68 h) than those with regional catheters (median 74 h, P = 0.006). CONCLUSIONS: INC was associated with longer operative times but decreased in-hospital OMEs when compared to bilateral regional block catheters and multimodal analgesia alone.

Combined Primary Resection with Hepatic Artery Infusion Pump Implantation Is Safe for Unresectable Colorectal Liver Metastases.

BACKGROUND: Colorectal liver metastases (CRLM) are the most common cause of disease-specific mortality in patients with colorectal cancer. Hepatic artery infusion (HAI) combined with systemic chemotherapy improves survival for these patients. The safety of colorectal resection at the time of HAI pump placement has not been well established. METHODS: Patients with CRLM who underwent combined HAI pump placement and colorectal (primary) resection or HAI pump placement alone were evaluated for perioperative outcomes, pump-specific complications, infectious complications, and time to treatment initiation. These outcomes were compared using comparative statistics. RESULTS: Patients who underwent combined HAI pump placement and primary resection (n = 19) vs HAI pump placement alone (n = 13) had similar demographics and rates of combined hepatectomy. Combined HAI pump placement and primary resection group had similar operative time and blood loss (both p = NS), but longer length of stay (6 vs 4 days, p = 0.02) compared to pump placement alone. Overall postoperative complications (21% vs 8%) and pump-specific complications (16% vs 31%) were similar (both p = NS). Infection rates were not different between groups, nor was time to initiation of HAI therapy (19 vs 16 days p = NS), or systemic therapy (34 vs 35 days p = NS). CONCLUSION: Combining colorectal resection with HAI pump implantation is a safe surgical approach for management of unresectable CRLM. Postoperative complications, specifically infectious complications, were not increased, nor was there a delay to initiation of HAI or systemic chemotherapy. Investigation of long-term oncologic outcomes for HAI pump placement and primary tumor resection in patients with unresectable CRLM is ongoing.

Coagulation Abnormalities and Clinical Complications in Children With SARS-CoV-2: A Systematic Review of 48,322 Patients.

Given the limited information on the coagulation abnormalities of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in pediatric patients, we designed a systematic review to evaluate this topic. A comprehensive literature search was conducted for "SARS-CoV-2," "coagulopathy," and "pediatrics." Two authors independently screened the articles that the search returned for bleeding, thrombosis, anticoagulant and/or antiplatelet usage, and abnormal laboratory markers in pediatric patients with SARS-CoV-2, and the authors then extracted the relevant data. One hundred twenty-six publications were included. Thirty-four (27%) studies reported thrombotic complications in 504 patients. Thirty-one (25%) studies reported bleeding complications in 410 patients. Ninety-eight (78%) studies reported abnormal laboratory values in 6580 patients. Finally, 56 (44%) studies reported anticoagulant and/or antiplatelet usage in 3124 patients. The variety of laboratory abnormalities and coagulation complications associated with SARS-CoV-2 presented in this review highlights the complexity and variability of the disease presentation in infants and children.

Disparities in neonatal abstinence syndrome and health insurance status: A statewide study using non-claims real-time surveillance data.

BACKGROUND: Most studies examining the relationship between neonatal abstinence syndrome (NAS) and health insurance status in the United States (USA) have used administrative insurance claims data, which is subject to myriad limitations. We examined the association between NAS and health insurance status in a large geographically defined rural population in the United States, using non-claims data. METHODS: We utilized data from a population-based cohort of all newborns born in 2017-2019 in the rural state of West Virginia (WV) and restricted analyses to WV residents' births (n = 46 213). NAS was defined as neonatal withdrawal from many substances, including opiates and not limited to those cases that require pharmacological treatment. RESULTS: Medicaid covered more than half (52.6%) of all infants' births in the state of WV. The incidence of NAS was 85.8 and 12.7 per 1000 livebirths in the Medicaid and privately insured groups, respectively. Among all infants diagnosed with NAS, 86.1% were enrolled in the state's Medicaid programme. The risk of NAS in the Medicaid-insured newborns was higher than privately insured newborns in the unadjusted analysis (risk ratio (RR) 6.76, 95% confidence interval (CI) 5.95, 7.68) and the adjusted analysis RR 3.00, 95% CI 2.01, 4.49); adjusted risk difference 20.3 (95% CI 17.5, 23.1 cases per 1000 livebirths). CONCLUSIONS: NAS is an important indicator of the immediate effect of the opioid crisis. This study shows the disparity in NAS by health insurance status for a large rural population in the United States, and its burden on the state's Medicaid programme. Providing timely and accurate estimates of NAS is important for public health policies and decision making.

Donor-Recipient Height Mismatch Is Associated With Decreased Survival in Pediatric-to-Adult Liver Transplant Recipients.

Liver grafts from pediatric donors represent a small fraction of grafts transplanted into adult recipients, and their use in adults requires special consideration of donor size to prevent perioperative complications. In the past, graft weight or volume ratios have been adopted from the living donor liver transplant literature to guide clinicians; however, these metrics are not regularly available to surgeons accepting deceased donor organs. In this study, we evaluated all pediatric-to-adult liver transplants in the United Network for Organ Sharing Standard Transplant Analysis and Research database from 1987 to 2019, stratified by donor age and donor-recipient height mismatch ratio (HMR; defined as donor height/recipient height). On multivariable regression controlling for cold ischemia time, age, and transplantation era, the use of donors from ages 0 to 4 and 5 to 9 had increased risk of graft failure (hazard ratio [HR], 1.81 [P < 0.01] and HR, 1.16 [P < 0.01], respectively) compared with donors aged 15 to 17. On Kaplan-Meier survival analysis, a HMR < 0.8 was associated with inferior graft survival (mean, 11.8 versus 14.6 years; log-rank P < 0.001) and inferior patient survival (mean, 13.5 versus 14.9 years; log-rank P < 0.01) when compared with pairs with similar height (HMR, 0.95-1.05; ie, donors within 5% of recipient height). This study demonstrates that both young donor age and low HMR confer additional risk in adult recipients of pediatric liver grafts.

Hematology and Depression Levels: Examining Correlated Factors Among Hospitalized Patients.

BACKGROUND: Depression in patients with cancer negatively influences physical symptoms, treatment success, coping, and quality of life (QOL), and is associated with increased mortality. OBJECTIVES: This study investigated the prevalence of depression and explored fatigue, QOL, and pain that is associated with depression in patients on first admission to a hematologic oncology unit. METHODS: This descriptive study measured depression, QOL, and fatigue with the Patient Health Questionnaire-9, the Functional Assessment of Cancer Therapy (FACT)-General, and the FACT-Anemia scale, respectively. Pain levels were examined with a numeric rating scale. FINDINGS: 58 patients participated; 17 reported moderate to severe depression, which highly correlated with fatigue, QOL, and pain. Among all factors, multivariate analysis showed that fatigue, particularly the physical domain of fatigue, has the strongest reverse correlation with depression.

Impact of Donor Brain Death Duration on Outcomes After Lung Transplantation.

BACKGROUND: Donor brain death duration (BDD) may impact posttransplant graft function and survival in lung transplant. METHODS: We queried the 2007 to 2018 United Network for Organ Sharing Registry for adult recipients undergoing first-time isolated lung transplant. Cox proportional hazard modeling with splines enabled identification of 3 donor brain death intervals for subsequent analysis: short (<24 hours), reference (24-60 hours), and long (>60 hours). The primary outcome was posttransplant survival. RESULTS: In total, 19,721 donors and recipients met inclusion criteria. Median time from donor brain death until cross-clamp was 36.6 hours (interquartile range, 19.5). Unadjusted overall survival between cohorts was equivalent (log-rank P = .42); however, longer BDD was associated with improved bronchiolitis obliterans syndrome (BOS)-free survival (log-rank P < .001). On multivariable Cox proportional hazards regression, BDD was not associated with recipient survival (P > .05). Similarly, logistic regression did not identify an independent association between BDD and primary graft dysfunction (P > .05). Increased BDD was, however, associated with a decreased risk of acute rejection (long vs reference; adjusted odds ratio, 0.78; 95% confidence interval, 0.64-0.94) and improved BOS-free survival (long vs reference; adjusted hazard ratio, 0.88; 95% confidence interval, 0.81-0.96). CONCLUSIONS: Donor BDD is not associated with posttransplant survival or primary graft dysfunction. Long donor BDD, however, is associated with a decreased risk for acute rejection and improved BOS-free survival. Therefore, lung allografts from donors with a prolonged length of time from brain death until explant should not be viewed less favorably by donor selection centers.

Challenging 30-day mortality as a site-specific quality metric in non-small cell lung cancer.

OBJECTIVE: The objective of this project was to assess the best measure for postoperative outcomes by comparing 30-day and 90-day mortality rates after surgery for non-small cell lung cancer using the National Cancer Database. Secondarily, hospital performance was examined at multiple postoperative intervals to assess changes in ranking based on mortality up to 1 year after surgery. METHODS: Patients who had undergone surgery for non-small cell lung cancer between 2004 and 2013 were identified in the National Cancer Database. Mortality rates at 30 days and 90 days were compared after adjusting for several patient characteristics, tumor variables, and hospital procedural volume using generalized logistic mixed models. Subsequently, mixed model logistic regression models were employed to evaluate hospital performance based on calculated mortality at prespecified time points. RESULTS: A total of 303,579 patients with non-small cell lung cancer were included for analysis. The 90-day mortality was almost double the 30-day mortality (3.0% vs 5.7%). Several patient characteristics, tumor features, and hospital volume were significantly associated with mortality at both 30 days and 90 days. Hospital rankings fluctuate appreciably between early mortality time points, which is additional evidence that quality metrics need to be based on later mortality time points. CONCLUSIONS: Thirty-day mortality is the commonly accepted quality measure for thoracic surgeons; however, hospital rankings may be inaccurate if based on this variable alone. Mortality after 90 days appears to be a threshold after which there is less variability in hospital ranking and should be considered as an alternative quality metric in lung cancer surgery.

Discovery and replication of SNP-SNP interactions for quantitative lipid traits in over 60,000 individuals.

BACKGROUND: The genetic etiology of human lipid quantitative traits is not fully elucidated, and interactions between variants may play a role. We performed a gene-centric interaction study for four different lipid traits: low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), total cholesterol (TC), and triglycerides (TG). RESULTS: Our analysis consisted of a discovery phase using a merged dataset of five different cohorts (n = 12,853 to n = 16,849 depending on lipid phenotype) and a replication phase with ten independent cohorts totaling up to 36,938 additional samples. Filters are often applied before interaction testing to correct for the burden of testing all pairwise interactions. We used two different filters: 1. A filter that tested only single nucleotide polymorphisms (SNPs) with a main effect of p < 0.001 in a previous association study. 2. A filter that only tested interactions identified by Biofilter 2.0. Pairwise models that reached an interaction significance level of p < 0.001 in the discovery dataset were tested for replication. We identified thirteen SNP-SNP models that were significant in more than one replication cohort after accounting for multiple testing. CONCLUSIONS: These results may reveal novel insights into the genetic etiology of lipid levels. Furthermore, we developed a pipeline to perform a computationally efficient interaction analysis with multi-cohort replication.

A biologically informed method for detecting rare variant associations.

BACKGROUND: BioBin is a bioinformatics software package developed to automate the process of binning rare variants into groups for statistical association analysis using a biological knowledge-driven framework. BioBin collapses variants into biological features such as genes, pathways, evolutionary conserved regions (ECRs), protein families, regulatory regions, and others based on user-designated parameters. BioBin provides the infrastructure to create complex and interesting hypotheses in an automated fashion thereby circumventing the necessity for advanced and time consuming scripting. PURPOSE OF THE STUDY: In this manuscript, we describe the software package for BioBin, along with type I error and power simulations to demonstrate the strengths and various customizable features and analysis options of this variant binning tool. RESULTS: Simulation testing highlights the utility of BioBin as a fast, comprehensive and expandable tool for the biologically-inspired binning and analysis of low-frequency variants in sequence data. CONCLUSIONS AND POTENTIAL IMPLICATIONS: The BioBin software package has the capability to transform and streamline the analysis pipelines for researchers analyzing rare variants. This automated bioinformatics tool minimizes the manual effort of creating genomic regions for binning such that time can be spent on the much more interesting task of statistical analyses. This software package is open source and freely available from http://ritchielab.com/software/biobin-download.

Characterization of the peptide binding specificity of the HLA class I alleles B*38:01 and B*39:06.

B*38:01 and B*39:06 are present with phenotypic frequencies <2% in the general population, but are of interest as B*39:06 is the B allele most associated with type 1 diabetes susceptibility and 38:01 is most protective. A previous study derived putative main anchor motifs for both alleles based on peptide elution data. The present study has utilized panels of single amino acid substitution peptide libraries to derive detailed quantitative motifs accounting for both primary and secondary influences on peptide binding. From these analyses, both alleles were confirmed to utilize the canonical position 2/C-terminus main anchor spacing. B*38:01 preferentially bound peptides with the positively charged or polar residues H, R, and Q in position 2 and the large hydrophobic residues I, F, L, W, and M at the C-terminus. B*39:06 had a similar preference for R in position 2, but also well-tolerated M, Q, and K. A more dramatic contrast between the two alleles was noted at the C-terminus, where the specificity of B*39:06 was clearly for small residues, with A as most preferred, followed by G, V, S, T, and I. Detailed position-by-position and residue-by-residue coefficient values were generated from the panels to provide detailed quantitative B*38:01 and B*39:06 motifs. It is hoped that these detailed motifs will facilitate the identification of T cell epitopes recognized in the context of two class I alleles associated with dramatically different dispositions towards type 1 diabetes, offering potential avenues for the investigation of the role of CD8 T cells in this disease.

Identifying gene-gene interactions that are highly associated with Body Mass Index using Quantitative Multifactor Dimensionality Reduction (QMDR).

BACKGROUND: Despite heritability estimates of 40-70 % for obesity, less than 2 % of its variation is explained by Body Mass Index (BMI) associated loci that have been identified so far. Epistasis, or gene-gene interactions are a plausible source to explain portions of the missing heritability of BMI. METHODS: Using genotypic data from 18,686 individuals across five study cohorts - ARIC, CARDIA, FHS, CHS, MESA - we filtered SNPs (Single Nucleotide Polymorphisms) using two parallel approaches. SNPs were filtered either on the strength of their main effects of association with BMI, or on the number of knowledge sources supporting a specific SNP-SNP interaction in the context of BMI. Filtered SNPs were specifically analyzed for interactions that are highly associated with BMI using QMDR (Quantitative Multifactor Dimensionality Reduction). QMDR is a nonparametric, genetic model-free method that detects non-linear interactions associated with a quantitative trait. RESULTS: We identified seven novel, epistatic models with a Bonferroni corrected p-value of association < 0.1. Prior experimental evidence helps explain the plausible biological interactions highlighted within our results and their relationship with obesity. We identified interactions between genes involved in mitochondrial dysfunction (POLG2), cholesterol metabolism (SOAT2), lipid metabolism (CYP11B2), cell adhesion (EZR), cell proliferation (MAP2K5), and insulin resistance (IGF1R). Moreover, we found an 8.8 % increase in the variance in BMI explained by these seven SNP-SNP interactions, beyond what is explained by the main effects of an index FTO SNP and the SNPs within these interactions. We also replicated one of these interactions and 58 proxy SNP-SNP models representing it in an independent dataset from the eMERGE study. CONCLUSION: This study highlights a novel approach for discovering gene-gene interactions by combining methods such as QMDR with traditional statistics.

The common equine class I molecule Eqca-1*00101 (ELA-A3.1) is characterized by narrow peptide binding and T cell epitope repertoires.

Here we describe a detailed quantitative peptide-binding motif for the common equine leukocyte antigen (ELA) class I allele Eqca-1*00101, present in roughly 25 % of Thoroughbred horses. We determined a preliminary binding motif by sequencing endogenously bound ligands. Subsequently, a positional scanning combinatorial library (PSCL) was used to further characterize binding specificity and derive a quantitative motif involving aspartic acid in position 2 and hydrophobic residues at the C-terminus. Using this motif, we selected and tested 9- and 10-mer peptides derived from the equine herpesvirus type 1 (EHV-1) proteome for their capacity to bind Eqca-1*00101. PSCL predictions were very efficient, with an receiver operating characteristic (ROC) curve performance of 0.877, and 87 peptides derived from 40 different EHV-1 proteins were identified with affinities of 500 nM or higher. Quantitative analysis revealed that Eqca-1*00101 has a narrow peptide-binding repertoire, in comparison to those of most human, non-human primate, and mouse class I alleles. Peripheral blood mononuclear cells from six EHV-1-infected, or vaccinated but uninfected, Eqca-1*00101-positive horses were used in IFN-γ enzyme-linked immunospot (ELISPOT) assays. When we screened the 87 Eqca-1*00101-binding peptides for T cell reactivity, only one Eqca-1*00101 epitope, derived from the intermediate-early protein ICP4, was identified. Thus, despite its common occurrence in several horse breeds, Eqca-1*00101 is associated with a narrow binding repertoire and a similarly narrow T cell response to an important equine viral pathogen. Intriguingly, these features are shared with other human and macaque major histocompatibility complex (MHC) molecules with a similar specificity for D in position 2 or 3 in their main anchor motif.

Acyclovir Has Low but Detectable Influence on HLA-B*57:01 Specificity without Inducing Hypersensitivity.

Immune mediated adverse drug reactions (IM-ADRs) remain a significant source of patient morbidity that have more recently been shown to be associated with specific class I and/or II human leukocyte antigen (HLA) alleles. Abacavir-induced hypersensitivity syndrome is a CD8+ T cell dependent IM-ADR that is exclusively mediated by HLA-B*57:01. We and others have previously shown that abacavir can occupy the floor of the peptide binding groove of HLA-B*57:01 molecules, increasing the affinity of certain self peptides resulting in an altered peptide-binding repertoire. Here, we have identified another drug, acyclovir, which appears to act in a similar fashion. As with abacavir, acyclovir showed a dose dependent increase in affinity for peptides with valine and isoleucine at their C-terminus. In agreement with the binding studies, HLA-B*57:01 peptide-elution studies performed in the presence of acyclovir revealed an increased number of endogenously bound peptides with a C-terminal isoleucine. Accordingly, we have hypothesized that acyclovir acts by the same mechanism as abacavir, although our data also suggest the overall effect is much smaller: the largest changes of peptide affinity for acyclovir were 2-5 fold, whereas for abacavir this effect was as much as 1000-fold. Unlike abacavir, acyclovir is not known to cause IM-ADRs. We conclude that the modest effect of acyclovir on HLA binding affinity in contrast to the large effect of abacavir is insufficient to trigger a hypersensitivity syndrome. We further support this by functional in vitro studies where acyclovir, unlike abacavir, was unable to produce an increase in IFN-γ upon expansion of HLA-B*57:01+ PBMCs from healthy donors. Using abacavir and acyclovir as examples we therefore propose an in vitro pre-clinical screening strategy, whereby thresholds can be applied to MHC-peptide binding assays to determine the likelihood that a drug could cause a clinically relevant IM-ADR.

Phenome-wide Association Study Relating Pretreatment Laboratory Parameters With Human Genetic Variants in AIDS Clinical Trials Group Protocols.

Background. Phenome-Wide Association Studies (PheWAS) identify genetic associations across multiple phenotypes. Clinical trials offer opportunities for PheWAS to identify pharmacogenomic associations. We describe the first PheWAS to use genome-wide genotypic data and to utilize human immunodeficiency virus (HIV) clinical trials data. As proof-of-concept, we focused on baseline laboratory phenotypes from antiretroviral therapy-naive individuals. Methods. Data from 4 AIDS Clinical Trials Group (ACTG) studies were split into 2 datasets: Dataset I (1181 individuals from protocol A5202) and Dataset II (1366 from protocols A5095, ACTG 384, and A5142). Final analyses involved 2547 individuals and 5 954 294 imputed polymorphisms. We calculated comprehensive associations between these polymorphisms and 27 baseline laboratory phenotypes. Results. A total of 10 584 (0.17%) polymorphisms had associations with P < .01 in both datasets and with the same direction of association. Twenty polymorphisms replicated associations with identical or related phenotypes reported in the Catalog of Published Genome-Wide Association Studies, including several not previously reported in HIV-positive cohorts. We also identified several possibly novel associations. Conclusions. These analyses define PheWAS properties and principles with baseline laboratory data from HIV clinical trials. This approach may be useful for evaluating on-treatment HIV clinical trials data for associations with various clinical phenotypes.

Next-generation analysis of cataracts: determining knowledge driven gene-gene interactions using biofilter, and gene-environment interactions using the Phenx Toolkit*.

Investigating the association between biobank derived genomic data and the information of linked electronic health records (EHRs) is an emerging area of research for dissecting the architecture of complex human traits, where cases and controls for study are defined through the use of electronic phenotyping algorithms deployed in large EHR systems. For our study, cataract cases and controls were identified within the Marshfield Personalized Medicine Research Project (PMRP) biobank and linked EHR, which is a member of the NHGRI-funded electronic Medical Records and Genomics (eMERGE) Network. Our goal was to explore potential gene-gene and gene-environment interactions within these data for 527,953 and 527,936 single nucleotide polymorphisms (SNPs) for gene-gene and gene-environment analyses, respectively, with minor allele frequency > 1%, in order to explore higher level associations with cataract risk beyond investigations of single SNP-phenotype associations. To build our SNP-SNP interaction models we utilized a prior-knowledge driven filtering method called Biofilter to minimize the multiple testing burden of exploring the vast array of interaction models possible from our extensive number of SNPs. Using Biofilter, we developed 57,376 prior-knowledge directed SNP-SNP models to test for association with cataract status. We selected models that required 6 sources of external domain knowledge. We identified 13 statistically significant SNP-SNP models with an interaction with p-value < 1 × 10(-4), as well as an overall model with p-value < 0.01 associated with cataract status. We also conducted gene-environment interaction analyses for all GWAS SNPs and a set of environmental factors from the PhenX Toolkit: smoking, UV exposure, and alcohol use;these environmental factors have been previously associated with the formation of cataracts. We found a total of 782 gene-environment models that exhibit an interaction with a p-value < 1 × 10(-4) associatedwith cataract status. Our results show these approaches enable advanced searches for epistasis and gene-environment interactions beyond GWAS, and that the EHR based approach provides an additional source of data for seeking these advanced explanatory models of the etiology of complex disease/outcome such as cataracts.

BioBin: a bioinformatics tool for automating the binning of rare variants using publicly available biological knowledge.

BACKGROUND: With the recent decreasing cost of genome sequence data, there has been increasing interest in rare variants and methods to detect their association to disease. We developed BioBin, a flexible collapsing method inspired by biological knowledge that can be used to automate the binning of low frequency variants for association testing. We also built the Library of Knowledge Integration (LOKI), a repository of data assembled from public databases, which contains resources such as: dbSNP and gene Entrez database information from the National Center for Biotechnology (NCBI), pathway information from Gene Ontology (GO), Protein families database (Pfam), Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, NetPath - signal transduction pathways, Open Regulatory Annotation Database (ORegAnno), Biological General Repository for Interaction Datasets (BioGrid), Pharmacogenomics Knowledge Base (PharmGKB), Molecular INTeraction database (MINT), and evolutionary conserved regions (ECRs) from UCSC Genome Browser. The novelty of BioBin is access to comprehensive knowledge-guided multi-level binning. For example, bin boundaries can be formed using genomic locations from: functional regions, evolutionary conserved regions, genes, and/or pathways. METHODS: We tested BioBin using simulated data and 1000 Genomes Project low coverage data to test our method with simulated causative variants and a pairwise comparison of rare variant (MAF < 0.03) burden differences between Yoruba individuals (YRI) and individuals of European descent (CEU). Lastly, we analyzed the NHLBI GO Exome Sequencing Project Kabuki dataset, a congenital disorder affecting multiple organs and often intellectual disability, contrasted with Complete Genomics data as controls. RESULTS: The results from our simulation studies indicate type I error rate is controlled, however, power falls quickly for small sample sizes using variants with modest effect sizes. Using BioBin, we were able to find simulated variants in genes with less than 20 loci, but found the sensitivity to be much less in large bins. We also highlighted the scale of population stratification between two 1000 Genomes Project data, CEU and YRI populations. Lastly, we were able to apply BioBin to natural biological data from dbGaP and identify an interesting candidate gene for further study. CONCLUSIONS: We have established that BioBin will be a very practical and flexible tool to analyze sequence data and potentially uncover novel associations between low frequency variants and complex disease.

Next-generation analysis of cataracts: determining knowledge driven gene-gene interactions using Biofilter, and gene-environment interactions using the PhenX Toolkit.

Investigating the association between biobank derived genomic data and the information of linked electronic health records (EHRs) is an emerging area of research for dissecting the architecture of complex human traits, where cases and controls for study are defined through the use of electronic phenotyping algorithms deployed in large EHR systems. For our study, 2580 cataract cases and 1367 controls were identified within the Marshfield Personalized Medicine Research Project (PMRP) Biobank and linked EHR, which is a member of the NHGRI-funded electronic Medical Records and Genomics (eMERGE) Network. Our goal was to explore potential gene-gene and gene-environment interactions within these data for 529,431 single nucleotide polymorphisms (SNPs) with minor allele frequency > 1%, in order to explore higher level associations with cataract risk beyond investigations of single SNP-phenotype associations. To build our SNP-SNP interaction models we utilized a prior-knowledge driven filtering method called Biofilter to minimize the multiple testing burden of exploring the vast array of interaction models possible from our extensive number of SNPs. Using the Biofilter, we developed 57,376 prior-knowledge directed SNP-SNP models to test for association with cataract status. We selected models that required 6 sources of external domain knowledge. We identified 5 statistically significant models with an interaction term with p-value < 0.05, as well as an overall model with p-value < 0.05 associated with cataract status. We also conducted gene-environment interaction analyses for all GWAS SNPs and a set of environmental factors from the PhenX Toolkit: smoking, UV exposure, and alcohol use; these environmental factors have been previously associated with the formation of cataracts. We found a total of 288 models that exhibit an interaction term with a p-value ≤ 1×10(-4) associated with cataract status. Our results show these approaches enable advanced searches for epistasis and gene-environment interactions beyond GWAS, and that the EHR based approach provides an additional source of data for seeking these advanced explanatory models of the etiology of complex disease/outcome such as cataracts.

Using BioBin to explore rare variant population stratification.

Rare variants (RVs) will likely explain additional heritability of many common complex diseases; however, the natural frequencies of rare variation across and between human populations are largely unknown. We have developed a powerful, flexible collapsing method called BioBin that utilizes prior biological knowledge using multiple publicly available database sources to direct analyses. Variants can be collapsed according to functional regions, evolutionary conserved regions, regulatory regions, genes, and/or pathways without the need for external files. We conducted an extensive comparison of rare variant burden differences (MAF < 0.03) between two ancestry groups from 1000 Genomes Project data, Yoruba (YRI) and European descent (CEU) individuals. We found that 56.86% of gene bins, 72.73% of intergenic bins, 69.45% of pathway bins, 32.36% of ORegAnno annotated bins, and 9.10% of evolutionary conserved regions (shared with primates) have statistically significant differences in RV burden. Ongoing efforts include examining additional regional characteristics using regulatory regions and protein binding domains. Our results show interesting variant differences between two ancestral populations and demonstrate that population stratification is a pervasive concern for sequence analyses.

Measurement of MHC/peptide interactions by gel filtration or monoclonal antibody capture.

This unit describes a technique for the direct and quantitative measurement of the capacity of peptide ligands to bind Class I and Class II MHC molecules. The binding of a peptide of interest to MHC is assessed based on its ability to inhibit the binding of a radiolabeled probe peptide to purified MHC molecules. This unit includes protocols for the purification of Class I and Class II MHC molecules by affinity chromatography, and for the radiolabeling of peptides using the chloramine T method. An alternate protocol describes alterations in the basic protocol that are necessary when performing direct binding assays, which are required for (1) selecting appropriate high-affinity, assay-specific, radiolabeled ligands, and (2) determining the amount of MHC necessary to yield assays with the highest sensitivity. After a predetermined incubation period, dependent upon the allele under examination, the bound and unbound radiolabeled species are separated, and their relative amounts are determined. Three methods for separation are described, two utilizing size-exclusion gel-filtration chromatography and a third using monoclonal antibody capture of MHC. Data analysis for each method is also explained.