A Multicenter Long-Term Cohort Study of Eosinophilic Esophagitis Variants and Their Progression to Eosinophilic Esophagitis Over Time

INTRODUCTION

Eosinophilic esophagitis (EoE) variants have been recently characterized as conditions with symptoms of esophageal dysfunction resembling EoE, but absence of significant esophageal eosinophilia. Their disease course and severity have yet to be determined.

METHODS

Patients from 6 EoE centers with symptoms of esophageal dysfunction, but peak eosinophil counts of <15/hpf in esophageal biopsies and absence of gastroesophageal reflux disease with at least one follow-up visit were included. Clinical, (immuno)histological, and molecular features were determined and compared with EoE and healthy controls.

RESULTS

We included 54 patients with EoE variants (EoE-like esophagitis 53.7%; lymphocytic esophagitis 13.0%; and nonspecific esophagitis 33.3%). In 8 EoE-like esophagitis patients, EoE developed after a median of 14 months (interquartile range 3.6-37.6). Such progression increased over time (17.6% year 1, 32.0% year 3, and 62.2% year 6). Sequential RNA sequencing analyses revealed only 7 genes associated with this progression (with TSG6 and ALOX15 among the top 3 upregulated genes) with upregulation of a previously attenuated Th2 pathway. Immunostaining confirmed the involvement of eosinophil-associated proteins (TSG6 and ALOX15) and revealed a significantly increased number of GATA3-positive cells during progression, indicating a Th1/Th2 switch. Transition from one EoE variant (baseline) to another variant (during follow-up) was seen in 35.2% (median observation time of 17.3 months).

DISCUSSION

Transition of EoE variants to EoE suggests the presence of a disease spectrum. Few genes seem to be associated with the progression to EoE with upregulation of a previously attenuated Th2 signal. These genes, including GATA3 as a Th1/Th2 switch regulator, may represent potential therapeutic targets in early disease pathogenesis.

Experimental validation of methods for differential gene expression analysis and sample pooling in RNA-seq

BACKGROUND

Massively parallel cDNA sequencing (RNA-seq) experiments are gradually superseding microarrays in quantitative gene expression profiling. However, many biologists are uncertain about the choice of differentially expressed gene (DEG) analysis methods and the validity of cost-saving sample pooling strategies for their RNA-seq experiments. Hence, we performed experimental validation of DEGs identified by Cuffdiff2, edgeR, DESeq2 and Two-stage Poisson Model (TSPM) in a RNA-seq experiment involving mice amygdalae micro-punches, using high-throughput qPCR on independent biological replicate samples. Moreover, we sequenced RNA-pools and compared their results with sequencing corresponding individual RNA samples.

RESULTS

False-positivity rate of Cuffdiff2 and false-negativity rates of DESeq2 and TSPM were high. Among the four investigated DEG analysis methods, sensitivity and specificity of edgeR was relatively high. We documented the pooling bias and that the DEGs identified in pooled samples suffered low positive predictive values.

CONCLUSIONS

Our results highlighted the need for combined use of more sensitive DEG analysis methods and high-throughput validation of identified DEGs in future RNA-seq experiments. They indicated limited utility of sample pooling strategies for RNA-seq in similar setups and supported increasing the number of biological replicate samples.