RNA Sequencing of Nasal Samples Used to Diagnose Asthma

A 90-gene biomarker panel has been established that enables the rapid, accurate diagnosis of asthma from simple nasal brush samples.

A nasal biomarker of asthma is of high interest given the accessibility of the nose and shared airway biology between the upper and lower respiratory tracts. The easily accessible nasal passages are directly connected to the lungs and exposed to common environmental factors.

In this regard, investigators at the Icahn School of Medicine at Mount Sinai (New York, NY, USA) sought to identify a nasal brush-based classifier of mild/moderate asthma. For this study, 190 subjects with mild/moderate asthma and controls underwent nasal brushing and RNA sequencing of the nasal samples.

The investigators used RNA sequencing (RNAseq) to comprehensively profile gene expression from nasal brushings collected from subjects with mild to moderate asthma and controls, creating the largest nasal RNAseq data set in asthma to date. They focused on mild to moderate asthma because the waxing and waning nature of non-severe asthma render it relatively difficult to diagnose.

Using a robust machine learning-based pipeline comprised of feature selection, classification, and statistical analyses, the investigators identified a 90-gene asthma classifier that accurately differentiated between subjects with and without mild-moderate asthma based on nasal brushings. They evaluated the classification performance of this asthma classifier on eight test sets of independent subjects with asthma and other respiratory conditions, finding that it performed with high accuracy, sensitivity, and specificity for asthma.

“Mild to moderate asthma can be difficult to diagnose because symptoms change over time and can be complicated by other respiratory conditions,” said senior author Dr. Supinda Bunyavanich, a physician and researcher at the Icahn School of Medicine at Mount Sinai. “Our nasal brush test takes seconds to collect. For time-strapped clinicians, particularly primary care providers at the front lines of asthma diagnosis, this could greatly improve patient outcomes through early and accurate diagnosis. With prospective validation in large cohorts, our asthma biomarker could lead to the development of a minimally invasive test to aid asthma diagnosis at clinical frontlines where time and resources often preclude pulmonary function testing.”

The asthma biomarker study was published in the June 11, 2018, online edition of the journal Scientific Reports.

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Icahn School of Medicine at Mount Sinai