Research in any field usually begins with a simple model that develops in complexity as more information and tools become available. In the area of genetics, many of the early studies, some of which examined the association between genetics and pain, began with the investigation of individual single-nucleotide polymorphisms (SNPs; a single DNA base change) that resulted in protein sequence changes that, in turn, were associated with an altered phenotypic expression. These early studies typically were individual SNP association trials examining a few of the usual suspect genes. Researchers would look for a particular individual SNP of interest and would correlate that with some independent variable, such as a pain score or the amount of medication required to control a patient’s pain. Of course, the human genome is composed of thousands of genes, and throughout the genome, there are an average of 2 to 3 million SNPs, varying from person to person. Although we learned many things from these studies, and still do, they are only the first phase in the evolution of trying to understand how the genome affects complex phenotypic behaviors, such as pain.
In this issue of Anesthesia & Analgesia, Fan et al.1 have taken the next important step in the evolution of association studies by looking at a group of SNPs, also called a haplotype, in the catechol-O-methyl transferase (COMT) gene. The COMT gene has been the focus of many studies in the area of pharmacogenomics and pain. The enzyme itself is responsible for degrading catecholamines, and genetic variants have been associated with changes in cognitive states, including executive functioning. SNPs in the COMT gene also have been reported previously to correlate with opioid consumption after surgery, and, more recently, investigators have been grouping SNPs together to obtain a more accurate understanding of how they combine to indicate a particular phenotype. This evolution of evaluating SNPs is the natural one; you look at one, then start combining them to form a complete picture.
Haplotype studies are harder to conduct than individual SNP studies for the simple reason that to get a sufficient number of subjects in each group, one typically requires many more patients than when looking at individual SNPs. Although the authors looked at only 4 SNPs, eventually it will be necessary to look at larger numbers; 1 SNP just cannot predict the pain phenotype with any certainty. Interestingly enough in this study, the authors did not find that any of the 4 COMT SNPs correlated with opioid consumption after surgery when the SNPs were evaluated individually; however, when they combined the SNPs to construct haplotypes, they were able to find a clear correlation between the haplotypes and opioid consumption.
It would only make sense that as more appropriate variables are added to any predictive model, that model should become more accurate. The desire to develop an accurate way to predict the pain phenotype has been around for awhile. In the end, if it is ever possible, a predictive model for pain will no doubt be composed of multiple variants from a variety of genes as well as environmental factors. In contrast to developing a complex genetic model, it has been suggested previously that simply asking a patient how much pain he or she will have after surgery also might be a good way to predict the pain phenotype. In 1 study, patients were able to accurately predict whether they would fall into a relatively high morphine use group or a low morphine use group after undergoing a nephrectomy.2 It is clear that understanding why and how people perceive pain and respond to pain medications is a crucial element of modern medicine; however, until we reach that goal, we may have to resort to the old medical practice of asking the patient, “How do you feel today?”
Name: Keith Candiotti, MD.
Contribution: This author helped write the manuscript.
Attestation: Keith Candiotti approved the final manuscript.
This manuscript was handled by: Spencer S. Liu, MD.
1. Zhang F, Tong J, Hu J, Zhang H, Ouyang W, Huang D, Tang Q, Liao Q. COMT gene haplotypes were closely associated with postoperative fentanyl dose in patients. Anesth Analg. 2015:120–933–40
2. Manjunath P, Rodríguez-Blanco YF, Gitlin MC, Candiotti KA. Patients can Predict the Severity of Acute Postoperative Pain.International Anesthesia Research Society, Control I.D. #1013021May 21–24, 2011Vancouver, Canada