The OpiOme: Integrating Omics Data with Psychometric Approaches to Assess Susceptibility to Opioid Use Disorder in Cancer Patients

Andres Filgueira

Mentor: Dr. L. Robert Gore and Dr. Zhihua Chen, Department of Biostatistics and Bioinformatics, and Dr. Brian Gonzalez, Department of Health Outcomes and Behavior, Moffitt Cancer Center.

Date/Time: April 30th, 2024 at 12pm.

Abstract: The opioid crisis represents a critical public health challenge. The OpiOme project, rooted in the understanding that Opioid Use Disorder (OUD) susceptibility varies significantly across individuals, seeks to assist with early detection and personalized intervention. Drawing from numerous genetic studies highlighting the role of specific single nucleotide polymorphisms (SNPs) and the intricate modulation of opioid receptors by endogenous and exogenous opioids, this project aims to integrate these biological insights with psychosocial factors, recognizing their profound impact on addiction pathways and behaviors. 

Leveraging data from over 600 participants derived from Moffitt Cancer Center’s ongoing PROSPECT study, we employed Item Response Theory (IRT) to enhance the measurement properties of a polygenic risk score (PRS). For this study we utilized a simple test, based on established psychological measuring techniques, to predict the risk of opioid dependency. The analysis revealed that our test could only explain a portion of the risk (about 25%) suggesting that it might not capture the full complexity of the issue. The consistency in the test’s items indicates that our method has potential, yet the overall results imply that other important factors affecting opioid risk were not included. This initial exploration highlights the need for further research using more comprehensive models as well as a larger dataset to improve prediction accuracy and draw more meaningful conclusions.