Pain sensitivity and opioid analgesia: a pharmacogenomic twin study

Twin studies of pain

Twin studies provide a method for estimating the heritability of phenotypes and for examining genetic and environmental relationships between phenotypes. We conducted a systematic review of twin studies of pain, including both clinical and experimental pain phenotypes. Fifty-six papers were included, whereof 52 addressed clinical phenotypes. Of the most comprehensively studied phenotypes, available data indicates heritability around 50% for migraine, tension-type headache and chronic widespread pain, around 35% for back and neck pain, and around 25% for irritable bowel syndrome. However, differences in phenotype definitions make these results somewhat uncertain. All clinical studies relied on dichotomous outcomes and none used pain intensity as continuous phenotype. This is a major weakness of the reviewed studies and gives reason to question their validity with respect to pain mechanisms. Experimental pain studies indicate large differences in heritability across pain modalities. Whereas there is evidence for substantial common genetic risk across many clinical pain conditions, different experimental pain phenotypes appear to be associated with different genetic factors. Recommendations for future research include inclusion of pain intensity scaling and number of pain sites in phenotyping. Furthermore, studies examining the genetic relationships between pain phenotypes, in particular between clinical and experimental phenotypes, should be prioritized.

Pharmacogenetics of pain and analgesia

Pain severity ratings and the analgesic dosing requirements of patients with apparently similar pain conditions may differ considerably between individuals. Contributing factors include those of genetic and environmental origin with epigenetic mechanisms that enable dynamic gene-environment interaction, more recently implicated in pain modulation. Insight into genetic factors underpinning inter-patient variability in pain sensitivity has come from rodent heritability studies as well as familial aggregation and twin studies in humans. Indeed, more than 350 candidate pain genes have been identified as potentially contributing to heritable differences in pain sensitivity. A large number of genetic association studies conducted in patients with a variety of clinical pain types or in humans exposed to experimentally induced pain stimuli in the laboratory setting, have examined the impact of single-nucleotide polymorphisms in various target genes on pain sensitivity and/or analgesic dosing requirements. However, the findings of such studies have generally failed to replicate or have been only partially replicated by independent investigators. Deficiencies in study conduct including use of small sample size, inappropriate statistical methods and inadequate attention to the possibility that between-study differences in environmental factors may alter pain phenotypes through epigenetic mechanisms, have been identified as being significant.

Integrative approach to pain genetics identifies pain sensitivity loci across diseases

Identifying human genes relevant for the processing of pain requires difficult-to-conduct and expensive large-scale clinical trials. Here, we examine a novel integrative paradigm for data-driven discovery of pain gene candidates, taking advantage of the vast amount of existing disease-related clinical literature and gene expression microarray data stored in large international repositories. First, thousands of diseases were ranked according to a disease-specific pain index (DSPI), derived from Medical Subject Heading (MESH) annotations in MEDLINE. Second, gene expression profiles of 121 of these human diseases were obtained from public sources. Third, genes with expression variation significantly correlated with DSPI across diseases were selected as candidate pain genes. Finally, selected candidate pain genes were genotyped in an independent human cohort and prospectively evaluated for significant association between variants and measures of pain sensitivity. The strongest signal was with rs4512126 (5q32, ABLIM3, P = 1.3×10⁻¹⁰) for the sensitivity to cold pressor pain in males, but not in females. Significant associations were also observed with rs12548828, rs7826700 and rs1075791 on 8q22.2 within NCALD (P = 1.7×10⁻⁴, 1.8×10⁻⁴, and 2.2×10⁻⁴ respectively). Our results demonstrate the utility of a novel paradigm that integrates publicly available disease-specific gene expression data with clinical data curated from MEDLINE to facilitate the discovery of pain-relevant genes. This data-derived list of pain gene candidates enables additional focused and efficient biological studies validating additional candidates.

The mechanisms underlying pain are incompletely understood, and are hard to study due to the subjective and complex nature of pain. From a genetics perspective, the discovery of genes relevant for the processing of pain in humans has been slow and genome-wide association studies have not been successful in yielding significantly associated variants. Targeted approaches examining specific candidate genes may be more promising. We present a novel integrative approach that combines publicly available molecular data and automatically extracted knowledge regarding pain contained in the literature to assist the discovery of novel pain genes. We prospectively validated this approach by demonstrating a significant association between several newly identified pain gene candidates and sensitivity to cold pressor pain.