Understanding the Big Picture of Precision Health in Anesthesia Care
Increased understanding of the genetic/genomic bases of diseases and response to treatment, coupled with rapid advances in new technology are reshaping our understanding of health care. Thanks to advances in computational analyses, we can process big data (genomic and electronic health records) to address the unmet needs in patients with variable responses to anesthesia. Precision health refers to the integration of the differences in people’s genetic make-up, environment, and lifestyle in all levels of health care from primary prevention to tertiary care. In April 2019, The AANA Journal Published a review article of the genetic bases of postoperative pain management.1
The authors describe the genetic basis of response to medications. Some commonly encountered terms include:
- Allele – versions of a gene that occur at a given point (locus). For most genes, a patient will have two copies, one maternal and one paternal allele. Some patients may have multiple alleles.
- Polymorphism – variation within a gene that occur in more than 1% of the population.
- Single nucleotide polymorphism (SNP) – most common type of genetic variation that involves variation at the level of an individual nucleotide.
- Genotype – the specific collection of genes (DNA sequence) of an individual
- Phenotype – the observable manifestation (physical traits) of the genotype
- Genome – the complete hereditary code (all the genes) in each individual or cell
- Pharmacogenetics/pharmacogenomics – use of pharmacologic and genetic/genomic data to predict response to medications.
Most drugs are metabolized by cytochrome p450 (CYP) enzymes. Thus, it is crucial to understand the nomenclature of CYP genes. For instance, NSAIDs are metabolized by CYP2C9 enzymes, coded by the CYP2C9 gene. Each patient’s genotype is usually reported as a star (*) allele, e.g., CYP2C9*1/*2. From left to right, the CYP implies cytochrome p450, 2 designate the family, C designates subfamily, 9 identifies the isoenzyme, and the *1 identifies the first allele, and *2 identifies the second allele. Note that unlike the enzyme, the abbreviations of various genes are italicized.
In conclusion, “implementation of pharmacogenomics into clinical practice is rapidly progressing in many institutions across the United States. As the cost of pharmacogenomic testing decreases and as direct-to-consumer testing increases, correct interpretation and utilization of actionable genetic information may become a standard of care.” Therefore, it is imperative that CRNAs formulating an anesthetic plan, or seeing patients with pain be knowledgeable about precision health.
- Aroke EN, Kittelsrud JM. A primer to pharmacogenetics of postoperative pain management. AANA Journal. 2019;87(2):131-137.
Dr. Aroke is Assistant Professor of Nurse Anesthesia, and Pain & Genomics Researcher at the University of Alabama at Birmingham. He received his Ph.D. from the University of Massachusetts Medical School with distinction; earning the 2016 Chancellor’s Award for his academic excellence, and clinical/community leadership. In 2011, he completed his Nurse Anesthesia education at Duke University Nurse Anesthesia Program in Durham, NC. Dr. Aroke is an active member of the American Association of Nurse Anesthetists (AANA), The Nursing Honors Society-Sigma Theta Tau International, and Alabama Association of Nurse Anesthetists (ALANA), and serves on both the NBCRNA Evaluation and Research Advisory Committee and the NBCRNA Continued Professional Certification Assessment Committee. He has published several peer-reviewed articles, and presented nationally and internationally on pharmacogenomics, pain management, and anesthesia outcomes.