RISE: Two-Stage Rank-Based Identification of High-Dimensional Surrogate Markers Applied to Vaccinology
Arthur Hughes, Layla Parast, Rodolphe Thi\'ebaut, Boris P. Hejblum

TL;DR
This paper introduces RISE, a novel rank-based method for identifying high-dimensional surrogate markers in vaccine trials, enabling early immune response inference and accelerating vaccine development.
Contribution
RISE is a new non-parametric approach tailored for small sample, high-dimensional data in vaccine studies, improving surrogate marker identification accuracy.
Findings
RISE controls type one error rate effectively.
Identified gene signatures as surrogate markers for immune response.
Pathways related to antiviral signaling were prominent.
Abstract
In vaccine trials with long-term participant follow-up, it is of great importance to identify surrogate markers that accurately infer long-term immune responses. These markers offer practical advantages such as providing early, indirect evidence of vaccine efficacy, and can accelerate vaccine development while identifying potential biomarkers. High-throughput technologies like RNA-sequencing have emerged as promising tools for understanding complex biological systems and informing new treatment strategies. However, these data are high-dimensional, presenting unique statistical challenges for existing surrogate marker identification methods. We introduce Rank-based Identification of high-dimensional SurrogatE Markers (RISE), a novel approach designed for small sample, high-dimensional settings typical in modern vaccine experiments. RISE employs a non-parametric univariate test to screen…
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Taxonomy
Topicsvaccines and immunoinformatics approaches · Viral gastroenteritis research and epidemiology · RNA and protein synthesis mechanisms
