Discovery and validation of biomarkers to aid the development of safe and effective pain therapeutics: challenges and opportunities.

Pain medication plays an important role in the treatment of acute and chronic pain conditions, but some drugs, opioids in particular, have been overprescribed or prescribed without adequate safeguards, leading to an alarming rise in medication-related overdose deaths. The NIH Helping to End Addiction Long-term (HEAL) Initiative is a trans-agency effort to provide scientific solutions to stem the opioid crisis. One component of the initiative is to support biomarker discovery and rigorous validation in collaboration with industry leaders to accelerate high-quality clinical research into neurotherapeutics and pain.

A functional polymorphism in the ATP-Binding Cassette B1 transporter predicts pharmacologic response to combination of nortriptyline and morphine in neuropathic pain patients.

Many genetic markers have been associated with variations in treatment response to analgesics, but none have been assessed in the context of combination therapies. In this study, the treatment effects of nortriptyline and morphine were tested for an association with genetic markers relevant to pain pathways. Treatment effects were determined for single and combination therapies.

Association of Catechol--methyltransferase single nucleotide polymorphisms, ethnicity, and sex in a large cohort of fibromyalgia patients.

Background: Fibromyalgia (FM) is a complex, centralized pain condition that is often difficult to diagnose and treat. FM is considered to have a genetic background due to its familial aggregation and due to findings from multiple candidate-gene studies implicating catecholaminergic and serotonergic neurotransmitter systems in chronic pain. However, a multi-factorial analysis of both genetic and environmental risk factors is lacking.

A Predictive Algorithm to Detect Opioid Use Disorder: What Is the Utility in a Primary Care Setting?

Purpose: The purpose of this study was to determine the clinical utility of an algorithm-based decision tool designed to assess risk associated with opioid use in the primary care setting.

Methods: A prospective, longitudinal study was conducted to assess the utility of precision medicine testing in 1822 patients across 18 family medicine/primary care clinics in the United States. Using the profile, patients were categorized into low, moderate, and high risk for opioid use.

A prospective, longitudinal study to evaluate the clinical utility of a predictive algorithm that detects risk of opioid use disorder.

Purpose: The purpose of this study was to determine the clinical utility of an algorithm-based decision tool designed to assess risk associated with opioid use. Specifically, we sought to assess how physicians were using the profile in patient care and how its use affected patient outcomes.

Patients And Methods: A prospective, longitudinal study was conducted to assess the utility of precision medicine testing in 5,397 patients across 100 clinics in the USA.

Validation Study of a Predictive Algorithm to Evaluate Opioid Use Disorder in a Primary Care Setting.

Background: Opioid abuse in chronic pain patients is a major public health issue. Primary care providers are frequently the first to prescribe opioids to patients suffering from pain, yet do not always have the time or resources to adequately evaluate the risk of opioid use disorder (OUD).

Purpose: This study seeks to determine the predictability of aberrant behavior to opioids using a comprehensive scoring algorithm ("profile") incorporating phenotypic and, more uniquely, genotypic risk factors.

Observational study to calculate addictive risk to opioids: a validation study of a predictive algorithm to evaluate opioid use disorder.

Background: Opioid abuse in chronic pain patients is a major public health issue, with rapidly increasing addiction rates and deaths from unintentional overdose more than quadrupling since 1999.

Purpose: This study seeks to determine the predictability of aberrant behavior to opioids using a comprehensive scoring algorithm incorporating phenotypic risk factors and neuroscience-associated single-nucleotide polymorphisms (SNPs).

Patients And Methods: The Proove Opioid Risk (POR) algorithm determines the predictability of aberrant behavior to opioids using a comprehensive scoring algorithm incorporating phenotypic risk factors and neuroscience-associated SNPs.

A precision medicine approach to a patient with unresolved pain following orthopedic surgery: a case report.

Background: Precision medicine is a promising technology in patient care that combines genetic analysis with clinical data, such as health, behavioral, functional, environment, and lifestyle information. Here we present the case of a 54-year old woman who, following an accident, had uncontrolled chronic pain and was subsequently labeled a drug seeker.

Case Presentation: A 54-year-old white woman who was experiencing severe calf pain was referred for treatment.

An observational study of the impact of genetic testing for pain perception in the clinical management of chronic non-cancer pain.

Objective: Pain levels are a key metric in clinical care. However, the assessment of pain is limited to basic questionnaires and physician interpretation, which yield subjective data. Genetic markers of pain sensitivity, such as single nucleotide polymorphisms in the catechol-O-methyltransferase gene, have been shown to be associated with pain perception and have been used to provide objective information about a patient's pain.

Engineered single nucleotide polymorphisms in the mosquito MEK docking site alter Plasmodium berghei development in Anopheles gambiae.

Background: Susceptibility to Plasmodium infection in Anopheles gambiae has been proposed to result from naturally occurring polymorphisms that alter the strength of endogenous innate defenses. Despite the fact that some of these mutations are known to introduce non-synonymous substitutions in coding sequences, these mutations have largely been used to rationalize knockdown of associated target proteins to query the effects on parasite development in the mosquito host. Here, we assay the effects of engineered mutations on an immune signaling protein target that is known to control parasite sporogonic development.