Jennifer E. Van Eyk

This paper evaluates the use of HTA protease in combination with trypsin for proteomic analysis, showing increased protein and modification identifications and improved quantification.

This study investigates the role of fast skeletal myosin binding protein-C in heart failure, finding that its expression exacerbates cardiac dysfunction and that its deletion improves heart function.

This paper introduces an enhanced single-cell proteomics workflow using timsUltra AIP, showing improved proteome coverage and drug response subtyping in human iPSC-CMs.

The paper reports single-cell proteomic maps of human iPSCs and their differentiation into motor neurons, revealing proteomic and transcriptomic discordance.

The paper develops a targeted LC-MS/MS assay for quantifying 60 plasma proteins in a health surveillance panel and applies it to detect disease-associated differences in chronic kidney disease.

This study introduces a shotgun single-cell top-down proteomics method to profile proteoform diversity in cardiomyocytes, revealing significant molecular heterogeneity across individual cells.

The paper introduces an algorithm called GoldenHaystack that improves peptide quantification in DIA-MS data by quantifying previously unquantified peptides and achieving faster runtime.

This study identifies two distinct cardiac proteomic signatures in HFpEF linked to sex ratios, revealing molecular differences in structural machinery and cellular communication.

This study identifies glycophagy dysregulation as a mechanism of diabetic heart disease and shows that Gabarapl1 gene therapy improves cardiac function in diabetic mice and human cardiac organoids.

The paper develops and evaluates a multiplexed PRM-MS assay for quantifying plasma proteins in an IBD cohort, demonstrating high quantifiability and consistent data acquisition.

This study provides a multiomics resource of cancer extracellular vesicles, showing correlations between LO proteins and prostate cancer progression, and demonstrating the feasibility of single-cell RNA-Seq on EVs.

This study compares the effects of HTT knockout and CAG repeat expansion in cortical neurons, identifying shared and distinct biological pathways involved in HD.

This paper develops a rapid proteomics method using HTA protease and LC-MS to quantify blood biomarkers in under an hour.

This study shows that cardiomyocyte stiffness contributes to diastolic dysfunction in cardiometabolic disease, identified through in vitro mechanical testing of isolated cardiomyocytes from mice with diet-induced disease.

This paper introduces TEAQ, a software tool that selects clinical-grade biomarker candidates from DIA-MS data by evaluating protein quantification metrics in a discovery cohort.

This paper introduces a high-throughput proteomics workflow using Orbitrap and Astral mass analyzers, demonstrating robust sample preparation and high protein identification rates across diverse biological samples.

This study shows that FTDP-17 mutations affect circTau RNA formation and translation, with ADAR1-p150 editing playing a key role in their expression and function.

The paper analyzes ATAC-seq data from iPSC-derived motor neurons of ALS patients and controls to identify disease-specific chromatin accessibility changes and their predictive power for disease progression.

ABDS provides tools for analyzing biologically diverse samples by addressing missing value imputation, signature gene detection, and expression pattern visualization.

This study adapts high-field asymmetric ion mobility spectrometry (FAIMS) coupled with mass spectrometry to improve cardiac muscle proteome coverage with reduced sample handling and processing time compared to traditional methods.

swCAM estimates subtype-specific expressions in individual samples using unsupervised deconvolution, revealing changes in cell proportions and gene expression in bipolar disorder.

This paper identifies key transcription and translation regulators affected by CDC treatment in rat HFpEF, correlating their levels with diastolic function improvements.

This study identifies Gabarapl1 as a regulator of glycophagy in diabetic cardiomyopathy, showing its role in preventing glycogen accumulation and diastolic dysfunction.

DDN2.0 provides R and Python tools for differential dependency network analysis to identify key pathways and network rewiring across omics data.

This paper introduces OVE-FC and OVE-sFC tests to detect subtype-specific and differentially expressed genes, showing improved accuracy in deconvolution compared to existing methods.

COT detects marker genes across subtypes using cosine similarity in a one-sample test, applicable to multi-omics data.

The paper performs an integrated multi-omic analysis of iPSC-derived motor neurons from C9ORF72 ALS patients to identify dysregulated pathways and validate them in vivo and in postmortem data.

This study shows that D2-HG induces cachexia in mice by disrupting NAD+ homeostasis and autophagy, revealing metabolic vulnerabilities in skeletal muscle.

The paper introduces a method to quantify lysine and arginine PTMs in NASH using mass spectrometry and applies it to mouse liver lysates, finding altered methylation and acetylation in NASH.