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.

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.

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).

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.

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 ( = 12,853 to  = 16,849 depending on lipid phenotype) and a replication phase with ten independent cohorts totaling up to 36,938 additional samples.

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.

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.

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.

Low frequency variants, collapsed based on biological knowledge, uncover complexity of population stratification in 1000 genomes project data.

Analyses investigating low frequency variants have the potential for explaining additional genetic heritability of many complex human traits. However, the natural frequencies of rare variation between human populations strongly confound genetic analyses. We have applied a novel collapsing method to identify biological features with low frequency variant burden differences in thirteen populations sequenced by the 1000 Genomes Project.

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.

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.

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.