Integrated molecular and multiparametric MRI mapping of high-grade glioma identifies regional biologic signatures.

Sampling restrictions have hindered the comprehensive study of invasive non-enhancing (NE) high-grade glioma (HGG) cell populations driving tumor progression. Here, we present an integrated multi-omic analysis of spatially matched molecular and multi-parametric magnetic resonance imaging (MRI) profiling across 313 multi-regional tumor biopsies, including 111 from the NE, across 68 HGG patients. Whole exome and RNA sequencing uncover unique genomic alterations to unresectable invasive NE tumor, including subclonal events, which inform genomic models predictive of geographic evolution.

Using Artificial Intelligence in Predicting Ischemic Stroke Events After Percutaneous Coronary Intervention.

Background: Ischemic stroke (IS) is an uncommon but severe complication in patients undergoing percutaneous coronary intervention (PCI). Despite significant morbidity and economic cost associated with post PCI IS, a validated risk prediction model is not currently available.

Aims: We aim to develop a machine learning model that predicts IS after PCI.

Performance comparisons of methylation and structural variants from low-input whole-genome methylation sequencing.

Whole-genome methylation sequencing carries both DNA methylation and structural variant information (single nucleotide variant [SNV]; copy number variant [CNV]); however, limited data is available on the reliability of obtaining this information simultaneously from low-input DNA using various library preparation and sequencing protocols. A HapMap NA12878 sample was sequenced with three protocols (EM-sequencing, QIA-sequencing and Swift-sequencing) and their performance was compared on CpG methylation measurement and SNV and CNV detection. At low DNA input (10-25 ng), EM-sequencing was superior in almost all metrics except CNV detection where all protocols were similar.

A New Insight Into Nonbacterial Thrombotic Endocarditis: A Systematic Review of Cases.

Background: Nonbacterial thrombotic endocarditis is characterized by the presence of organized thrombi on cardiac valves, often associated with hypercoagulable states. There is a paucity of data regarding the predictors of mortality in patients with nonbacterial thrombotic endocarditis. Our primary aim was to identify predictors of in-hospital mortality in patients with nonbacterial thrombotic endocarditis.

Integrating Transcriptomics, Genomics, and Imaging in Alzheimer's Disease: A Federated Model.

Alzheimer's disease (AD) affects more than 1 in 9 people age 65 and older and becomes an urgent public health concern as the global population ages. In clinical practice, structural magnetic resonance imaging (sMRI) is the most accessible and widely used diagnostic imaging modality. Additionally, genome-wide association studies (GWAS) and transcriptomics-the study of gene expression-also play an important role in understanding AD etiology and progression.

ω-3PUFA supplementation ameliorates adipose tissue inflammation and insulin-stimulated glucose disposal in subjects with obesity: a potential role for apolipoprotein E.

Background: Long chain omega-3 polyunsaturated fatty acids (ω-3PUFA) supplementation in animal models of diet-induced obesity has consistently shown to improve insulin sensitivity. The same is not always reported in human studies with insulin resistant (IR) subjects with obesity.

Objective: We studied whether high-dose ω-3PUFA supplementation for 3 months improves insulin sensitivity and adipose tissue (AT) inflammation in IR subjects with obesity.

National Cardiovascular Data Registry Model Predicts Long-Term Mortality in Patients Undergoing Percutaneous Coronary Interventions.

National Cardiovascular Data Registry (NCDR)-based logistic regression model is available for clinicians to predict in-hospital all-cause mortality after a percutaneous coronary intervention (PCI). However, this model has never been used to predict long-term all-cause mortality after PCI. Therefore, we sought to test the ability of the NCDR model to predict the short- and long-term risk of all-cause mortality in patients undergoing PCI.

Uncertainty quantification in the radiogenomics modeling of EGFR amplification in glioblastoma.

Radiogenomics uses machine-learning (ML) to directly connect the morphologic and physiological appearance of tumors on clinical imaging with underlying genomic features. Despite extensive growth in the area of radiogenomics across many cancers, and its potential role in advancing clinical decision making, no published studies have directly addressed uncertainty in these model predictions. We developed a radiogenomics ML model to quantify uncertainty using transductive Gaussian Processes (GP) and a unique dataset of 95 image-localized biopsies with spatially matched MRI from 25 untreated Glioblastoma (GBM) patients.

Ultrafast and scalable variant annotation and prioritization with big functional genomics data.

The advances of large-scale genomics studies have enabled compilation of cell type-specific, genome-wide DNA functional elements at high resolution. With the growing volume of functional annotation data and sequencing variants, existing variant annotation algorithms lack the efficiency and scalability to process big genomic data, particularly when annotating whole-genome sequencing variants against a huge database with billions of genomic features. Here, we develop VarNote to rapidly annotate genome-scale variants in large and complex functional annotation resources.

Comparison of echocardiographic parameters with cardiac magnetic resonance imaging in the assessment of right ventricular function.

Introduction: The right ventricle (RV) strain measured by speckle tracking (RVS) is an echocardiographic parameter used to assess RV function. We compared RVS to RV fractional area change (FAC%), tricuspid annular plane systolic excursion (TAPSE) and Doppler tissue imaging-derived peak systolic velocity (S') in the assessment of right ventricular (RV) systolic function measured using cardiac magnetic resonance imaging (MRI).

Methods: We enrolled consecutive patients who underwent cardiac MRI between Jan 2012 and Dec 2017 and a transthoracic echocardiogram (TTE) within 1 month of the MRI with no interval event.

Does a Gradient-Adjusted Cardiac Power Index Improve Prediction of Post-Transcatheter Aortic Valve Replacement Survival Over Cardiac Power Index?

Purpose: Cardiac power (CP) index is a product of mean arterial pressure (MAP) and cardiac output (CO). In aortic stenosis, however, MAP is not reflective of true left ventricular (LV) afterload. We evaluated the utility of a gradient-adjusted CP (GCP) index in predicting survival after transcatheter aortic valve replacement (TAVR), compared to CP alone.

"Direct to Drug" screening as a precision medicine tool in multiple myeloma.

Seventy-six FDA-approved oncology drugs and emerging therapeutics were evaluated in 25 multiple myeloma (MM) and 15 non-Hodgkin's lymphoma cell lines and in 113 primary MM samples. Ex vivo drug sensitivities were mined for associations with clinical phenotype, cytogenetic, genetic mutation, and transcriptional profiles. In primary MM samples, proteasome inhibitors, dinaciclib, selinexor, venetoclax, auranofin, and histone deacetylating agents had the broadest cytotoxicity.

Resting Cardiac Efficiency Affects Survival Following Transcatheter Aortic Valve Replacement.

Objective: Cardiac power to left ventricular mass (LVM) ratio, also termed cardiac efficiency (CE), reflects the rate of cardiac work delivered to the potential energy stored in LVM. We sought to assess the association between baseline resting CE and survival post transcatheter aortic valve replacement (TAVR).

Methods: We retrospectively extracted data of patients who received TAVR in the Mayo Clinic Foundation with follow up data available at 1 year.

Does Resting Cardiac Power Index Affect Survival Post Transcatheter Aortic Valve Replacement?

Objective: Cardiac power index (CPI) is an integrative hemodynamic measure of cardiac pumping capability and is the product of the simultaneously measured mean arterial pressure and the cardiac output. We assessed the association between baseline resting CPI and survival post transcatheter aortic valve replacement (TAVR).

Methods And Results: We retrospectively abstracted data of patients who underwent TAVR at the Mayo Clinic Foundation with follow-up data available at 1 year.

Integrated RNA-seq and ChIP-seq analysis reveals a feed-forward loop regulating H3K9ac and key labor drivers in human placenta.

Background: Chromatin alterations are important mediators of gene expression changes. We have recently shown that activated non-canonical NF-κB signaling (RelB/p52) recruits histone acetyltransferase CBP and deacetylase HDAC1 to selectively acetylate H3K9 (H3K9ac) to induce expression of corticotropin-releasing hormone (CRH) and prostaglandin-endoperoxide synthase-2 (PTGS2) in the human placenta. Both of these genes play a role in initiating parturition in human pregnancy.

GWAS4D: multidimensional analysis of context-specific regulatory variant for human complex diseases and traits.

Genome-wide association studies have generated over thousands of susceptibility loci for many human complex traits, and yet for most of these associations the true causal variants remain unknown. Tissue/cell type-specific prediction and prioritization of non-coding regulatory variants will facilitate the identification of causal variants and underlying pathogenic mechanisms for particular complex diseases and traits. By leveraging recent large-scale functional genomics/epigenomics data, we develop an intuitive web server, GWAS4D (http://mulinlab.

Colonoscopy surveillance for high risk polyps does not always prevent colorectal cancer.

Aim: To determine the frequency and risk factors for colorectal cancer (CRC) development among individuals with resected advanced adenoma (AA)/traditional serrated adenoma (TSA)/advanced sessile serrated adenoma (ASSA).

Methods: Data was collected from medical records of 14663 subjects found to have AA, TSA, or ASSA at screening or surveillance colonoscopy. Patients with inflammatory bowel disease or known genetic predisposition for CRC were excluded from the study.

Molecular characterization of colorectal adenomas with and without malignancy reveals distinguishing genome, transcriptome and methylome alterations.

The majority of colorectal cancer (CRC) arises from precursor lesions known as polyps. The molecular determinants that distinguish benign from malignant polyps remain unclear. To molecularly characterize polyps, we utilized Cancer Adjacent Polyp (CAP) and Cancer Free Polyp (CFP) patients.

Discovery of Surface Target Proteins Linking Drugs, Molecular Markers, Gene Regulation, Protein Networks, and Disease by Using a Web-Based Platform Targets-search.

Integration and analysis of high content omics data have been critical to the investigation of molecule interactions (e.g., DNA-protein, protein-protein, chemical-protein) in biological systems.

Linnorm: improved statistical analysis for single cell RNA-seq expression data.

Linnorm is a novel normalization and transformation method for the analysis of single cell RNA sequencing (scRNA-seq) data. Linnorm is developed to remove technical noises and simultaneously preserve biological variations in scRNA-seq data, such that existing statistical methods can be improved. Using real scRNA-seq data, we compared Linnorm with existing normalization methods, including NODES, SAMstrt, SCnorm, scran, DESeq and TMM.

mTCTScan: a comprehensive platform for annotation and prioritization of mutations affecting drug sensitivity in cancers.

Cancer therapies have experienced rapid progress in recent years, with a number of novel small-molecule kinase inhibitors and monoclonal antibodies now being widely used to treat various types of human cancers. During cancer treatments, mutations can have important effects on drug sensitivity. However, the relationship between tumor genomic profiles and the effectiveness of cancer drugs remains elusive.

Exploring genetic associations with ceRNA regulation in the human genome.

Competing endogenous RNAs (ceRNAs) are RNA molecules that sequester shared microRNAs (miRNAs) thereby affecting the expression of other targets of the miRNAs. Whether genetic variants in ceRNA can affect its biological function and disease development is still an open question. Here we identified a large number of genetic variants that are associated with ceRNA's function using Geuvaids RNA-seq data for 462 individuals from the 1000 Genomes Project.

cepip: context-dependent epigenomic weighting for prioritization of regulatory variants and disease-associated genes.

It remains challenging to predict regulatory variants in particular tissues or cell types due to highly context-specific gene regulation. By connecting large-scale epigenomic profiles to expression quantitative trait loci (eQTLs) in a wide range of human tissues/cell types, we identify critical chromatin features that predict variant regulatory potential. We present cepip, a joint likelihood framework, for estimating a variant's regulatory probability in a context-dependent manner.