Examination of eQTL Polymorphisms Associated with Increased Risk of Progressive Complicated Sarcoidosis in European and African Descent Subjects.

Background: A limited pool of SNPs are linked to the development and severity of sarcoidosis, a systemic granulomatous inflammatory disease. By integrating genome-wide association studies (GWAS) data and expression quantitative trait loci (eQTL) single nuclear polymorphisms (SNPs), we aimed to identify novel sarcoidosis SNPs potentially influencing the development of complicated sarcoidosis.

Methods: A GWAS (Affymetrix 6.

Accounting for extra-binomial variability with differentially expressed genetic pathway data: a collaborative bioinformatic study.

We describe a collaborative project involving faculty and students in a university bioinformatics/biostatistics center. The project focuses on identification of differentially expressed gene sets ("pathways") in subjects expressing a disease state, medical intervention, or other distinguishable condition. The key feature of the endeavor is the data structure presented to the team: a single cohort of subjects with two samples taken from each subject - one for each of two differing conditions without replication.

Epithelial cell responses to rhinovirus identify an early-life-onset asthma phenotype in adults.

Background: The study of pathogenic mechanisms in adult asthma is often marred by a lack of precise information about the natural history of the disease. Children who have persistent wheezing (PW) during the first 6 years of life and whose symptoms start before age 3 years (PW) are much more likely to have wheezing illnesses due to rhinovirus (RV) in infancy and to have asthma into adult life than are those who do not have PW (PW).

Objective: Our aim was to determine whether nasal epithelial cells from PW asthmatic adults as compared with cells from PW asthmatic adults show distinct biomechanistic processes activated by RV exposure.

Endothelial eNAMPT drives EndMT and preclinical PH: rescue by an eNAMPT-neutralizing mAb.

Pharmacologic interventions to halt/reverse the vascular remodeling and right ventricular dysfunction in pulmonary arterial hypertension (PAH) remains an unmet need. We previously demonstrated extracellular nicotinamide phosphoribosyltransferase (eNAMPT) as a DAMP (damage-associated molecular pattern protein) contributing to PAH pathobiology via TLR4 ligation. We examined the role of endothelial cell (EC)-specific eNAMPT in experimental PH and an eNAMPT-neutralizing mAb as a therapeutic strategy to reverse established PH.

'Single-subject studies'-derived analyses unveil altered biomechanisms between very small cohorts: implications for rare diseases.

Motivation: Identifying altered transcripts between very small human cohorts is particularly challenging and is compounded by the low accrual rate of human subjects in rare diseases or sub-stratified common disorders. Yet, single-subject studies (S3) can compare paired transcriptome samples drawn from the same patient under two conditions (e.g.

Comparison and impact of COVID-19 for patients with cancer: a survival analysis of fatality rate controlling for age, sex and cancer type.

Objectives: Prior research has reported an increased risk of fatality for patients with cancer, but most studies investigated the risk by comparing cancer to non-cancer patients among COVID-19 infections, where cancer might have contributed to the increased risk. This study is to understand COVID-19's imposed HR of fatality while controlling for covariates, such as age, sex, metastasis status and cancer type.

Methods: We conducted survival analyses of 4606 cancer patients with COVID-19 test results from 16 March to 11 October 2020 in UK Biobank and estimated the overall HR of fatality with and without COVID-19 infection.

Personalized beyond Precision: Designing Unbiased Gold Standards to Improve Single-Subject Studies of Personal Genome Dynamics from Gene Products.

Developing patient-centric baseline standards that enable the detection of clinically significant outlier gene products on a genome-scale remains an unaddressed challenge required for advancing personalized medicine beyond the small pools of subjects implied by "precision medicine". This manuscript proposes a novel approach for reference standard development to evaluate the accuracy of single-subject analyses of transcriptomes and offers extensions into proteomes and metabolomes. In evaluation frameworks for which the distributional assumptions of statistical testing imperfectly model genome dynamics of gene products, artefacts and biases are confounded with authentic signals.

Differential transcriptomics in sarcoidosis lung and lymph node granulomas with comparisons to pathogen-specific granulomas.

Rationale: Despite the availability of multi-"omics" strategies, insights into the etiology and pathogenesis of sarcoidosis have been elusive. This is partly due to the lack of reliable preclinical models and a paucity of validated biomarkers. As granulomas are a key feature of sarcoidosis, we speculate that direct genomic interrogation of sarcoid tissues, may lead to identification of dysregulated gene pathways or biomarker signatures.

Correction to: binomialRF: interpretable combinatoric efficiency of random forests to identify biomarker interactions.

An amendment to this paper has been published and can be accessed via the original article.

binomialRF: interpretable combinatoric efficiency of random forests to identify biomarker interactions.

Background: In this era of data science-driven bioinformatics, machine learning research has focused on feature selection as users want more interpretation and post-hoc analyses for biomarker detection. However, when there are more features (i.e.

MicroRNA and protein-coding gene expression analysis in idiopathic pulmonary fibrosis yields novel biomarker signatures associated to survival.

Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive interstitial lung disease of unknown etiology that poses significant challenges in early diagnosis and prediction of progression. Analyses of microRNA and gene expression in IPF have yielded potentially predictive information. However, the relationship between microRNA/gene expression and quantitative phenotypic value in IPF remains controversial, as is the added value of this approach to current molecular signatures in IPF.

Interpretation of 'Omics dynamics in a single subject using local estimates of dispersion between two transcriptomes.

Calculating Differentially Expressed Genes (DEGs) from RNA-sequencing requires replicates to estimate gene-wise variability, a requirement that is at times financially or physiologically infeasible in clinics. By imposing restrictive transcriptome-wide assumptions limiting inferential opportunities of conventional methods (edgeR, NOISeq-sim, DESeq, DEGseq), comparing two conditions without replicates (TCWR) has been proposed, but not evaluated. Under TCWR conditions (e.

Development of a biomarker mortality risk model in acute respiratory distress syndrome.

Background: There is a compelling unmet medical need for biomarker-based models to risk-stratify patients with acute respiratory distress syndrome. Effective stratification would optimize participant selection for clinical trial enrollment by focusing on those most likely to benefit from new interventions. Our objective was to develop a prognostic, biomarker-based model for predicting mortality in adult patients with acute respiratory distress syndrome.

The mechanism of cancer drug addiction in ALK-positive T-Cell lymphoma.

Rational new strategies are needed to treat tumors resistant to kinase inhibitors. Mechanistic studies of resistance provide fertile ground for development of new approaches. Cancer drug addiction is a paradoxical resistance phenomenon, well-described in MEK-ERK-driven solid tumors, in which drug-target overexpression promotes resistance but a toxic overdose of signaling if the inhibitor is withdrawn.

Evaluating single-subject study methods for personal transcriptomic interpretations to advance precision medicine.

Background: Gene expression profiling has benefited medicine by providing clinically relevant insights at the molecular candidate and systems levels. However, to adopt a more 'precision' approach that integrates individual variability including 'omics data into risk assessments, diagnoses, and therapeutic decision making, whole transcriptome expression needs to be interpreted meaningfully for single subjects. We propose an "all-against-one" framework that uses biological replicates in isogenic conditions for testing differentially expressed genes (DEGs) in a single subject (ss) in the absence of an appropriate external reference standard or replicates.

A Single-Subject Method to Detect Pathways Enriched With Alternatively Spliced Genes.

RNA-Sequencing data offers an opportunity to enable precision medicine, but most methods rely on gene expression alone. To date, no methodology exists to identify and interpret alternative splicing patterns within pathways for an individual patient. This study develops methodology and conducts computational experiments to test the hypothesis that pathway aggregation of subject-specific alternatively spliced genes (ASGs) can inform upon disease mechanisms and predict survival.

Workshop during the Pacific Symposium of Biocomputing, Jan 3-7, 2019: Reading between the genes: interpreting non-coding DNA in high-throughput.

Identifying functional elements and predicting mechanistic insight from non-coding DNA and noncoding variation remains a challenge. Advances in genome-scale, high-throughput technology, however, have brought these answers closer within reach than ever, though there is still a need for new computational approaches to analysis and integration. This workshop aims to explore these resources and new computational methods applied to regulatory elements, chromatin interactions, non-protein-coding genes, and other non-coding DNA.

Precision drug repurposing via convergent eQTL-based molecules and pathway targeting independent disease-associated polymorphisms.

Repurposing existing drugs for new therapeutic indications can improve success rates and streamline development. Use of large-scale biomedical data repositories, including eQTL regulatory relationships and genome-wide disease risk associations, offers opportunities to propose novel indications for drugs targeting common or convergent molecular candidates associated to two or more diseases. This proposed novel computational approach scales across 262 complex diseases, building a multi-partite hierarchical network integrating (i) GWAS-derived SNP-to-disease associations, (ii) eQTL-derived SNP-to-eGene associations incorporating both cis- and trans-relationships from 19 tissues, (iii) protein target-to-drug, and (iv) drug-to-disease indications with (iv) Gene Ontology-based information theoretic semantic (ITS) similarity calculated between protein target functions.

Novel disease syndromes unveiled by integrative multiscale network analysis of diseases sharing molecular effectors and comorbidities.

Background: Forty-two percent of patients experience disease comorbidity, contributing substantially to mortality rates and increased healthcare costs. Yet, the possibility of underlying shared mechanisms for diseases remains not well established, and few studies have confirmed their molecular predictions with clinical datasets.

Methods: In this work, we integrated genome-wide association study (GWAS) associating diseases and single nucleotide polymorphisms (SNPs) with transcript regulatory activity from expression quantitative trait loci (eQTL).

ICD-10 procedure codes produce transition challenges.

The transition of procedure coding from ICD-9-CM-Vol-3 to ICD-10-PCS has generated problems for the medical community at large resulting from the lack of clarity required to integrate two non-congruent coding systems. We hypothesized that quantifying these issues with network topology analyses offers a better understanding of the issues, and therefore we developed solutions (online tools) to empower hospital administrators and researchers to address these challenges. Five topologies were identified: "identity"(I), "class-to-subclass"(C2S), "subclass-toclass"(S2C), "convoluted(C)", and "no mapping"(NM).

Word-of-Mouth Innovation: Hypothesis Generation for Supplement Repurposing based on Consumer Reviews.

Dietary supplements remain a relatively underexplored source for drug repurposing. A systematic approach to soliciting responses from a large consumer population is desirable to speed up innovation. We tested a workflow that mines unexpected benefits of dietary supplements from massive consumer reviews.

Physician nurse care: A new use of UMLS to measure professional contribution: Are we talking about the same patient a new graph matching algorithm?

Background: Physician and nurses have worked together for generations; however, their language and training are vastly different; comparing and contrasting their work and their joint impact on patient outcomes is difficult in light of this difference. At the same time, the EHR only includes the physician perspective via the physician-authored discharge summary, but not nurse documentation. Prior research in this area has focused on collaboration and the usage of similar terminology.

Genome-Wide Association Study in African Americans with Acute Respiratory Distress Syndrome Identifies the Selectin P Ligand Gene as a Risk Factor.

Rationale: Genetic factors are involved in acute respiratory distress syndrome (ARDS) susceptibility. Identification of novel candidate genes associated with increased risk and severity will improve our understanding of ARDS pathophysiology and enhance efforts to develop novel preventive and therapeutic approaches.

Objectives: To identify genetic susceptibility targets for ARDS.