Pharmacogenomics and Pharmacometabolomics in Precision Tramadol Prescribing for Enhanced Pain Management: Evidence from QBB and EMR Data

TL;DR

This study explores how genetic and metabolic factors influence tramadol effectiveness and safety, aiming to improve personalized pain management.

Contribution

The study integrates pharmacogenomic and metabolomic data to identify tramadol's metabolic signatures and genetic influences on its efficacy.

Findings

CYP2D6 genetic variants significantly affect tramadol and O-desmethyltramadol glucuronide levels in normal metabolizers.

Tramadol users showed distinct metabolic profiles with changes in phosphatidylcholine, histidine, and lysine pathways.

Chronic pain was the primary reason for tramadol prescriptions, followed by acute pain, according to EMR data.

Abstract

Background/Objectives: Tramadol is an opioid frequently prescribed for moderate to severe pain and has seen a global increase in use. This presents numerous challenges in clinical management. This study aims to elucidate metabolic signatures associated with tramadol consumption, enhancing predictive capabilities for therapeutic outcomes and optimizing patient-specific treatment plans. Methods: Data were obtained from the Qatar Biobank (QBB), focusing on pharmacogenomic variants associated with tramadol use and prescription trends. A cohort of 27 individuals who were administered daily tramadol doses between 100 and 400 mg with available metabolomic profiles were selected. The pharmacokinetics of tramadol were evaluated in relation to specific CYP2D6 genetic variants. Comparative pharmacometabolomic profiles were generated for tramadol users versus a control group of 54 non-users. Additionally, prescription data encompassing tramadol formulations were collected from the electronic medical records (EMR) system of the major public hospital network in Qatar (Hamad Medical Corporation) to discern prescribing patterns. Results: From January 2019 to December 2022, tramadol prescriptions varied, with chronic pain as the primary indication, followed by acute pain. Pharmacogenomic analysis indicated that CYP2D6 allele variations significantly impacted tramadol and O-desmethyltramadol glucuronide levels, notably in ‘normal metabolizers’. Metabolomic analysis revealed distinct metabolic profiles in tramadol users, with significant variations in phosphatidylcholine, histidine, and lysine pathways compared to controls, highlighting tramadol’s unique biochemical impacts. Conclusions: This study underscores the importance of integrating genetic and omics-based approaches to enhance tramadol’s efficacy and safety. These findings support personalized pain management strategies, enhancing treatment outcomes for both chronic and acute pain.

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