Outcomes after traumatic injury, perhaps more than in any other surgical disease, have improved through standardization of care. Nevertheless and despite seemingly ideal care, unexpected outcomes occur. Why do patients with similar injuries or severity of acute illness, despite receiving comparable and appropriate treatment, often follow different paths? While one patient recovers uneventfully from massive transfusion for hemorrhagic shock after a motor vehicle collision, another follows a prolonged course complicated by nosocomial pneumonia and organ failure. Consider also, the seemingly more straightforward task of preventing or treating deep venous thromboembolic disease. Despite our understanding of the biology of coagulation and pharmacotherapeutic strategies, venous thromboses and pulmonary emboli still occur, often with fatal consequences.

Numerous clinical, environmental, and genetic factors contribute to variability in the inflammatory response, variable rates of drug metabolism and risk for venous thromboembolic disease. The completion of the Human Genome Project and technological advances in sequencing and small molecule identification have provided the foundation on which to build knowledge of genetic variation in both humans and animal models.¹ This, in turn, has been used to establish genotype–phenotype associations for common polygenic diseases, such as diabetes mellitus, cancer, and hypertension. Using this genetic variability to understand disease biology and to better direct therapy (such as drug selection and dosing) are the goals of the field of “genomic medicine.”² Understanding the information contained in an individual’s genetic fingerprint has the potential for further decreasing the disability and mortality secondary to traumatic injury.

At the molecular level, differences in DNA sequence can alter RNA transcription and protein translation, which thereby alter clinical phenotypes. For instance, drug absorption, metabolism, and excretion are all affected by genetic variation and are the focus of an emerging field of study called pharmacogenomics. The fields of proteomics and metabolomics are additional pieces of systems biology that are promising new discoveries and improvements in patient care. Taken together these form the foundation of personalized medicine. This chapter focuses on select aspects of these fields and their potential application to the care of critically ill and injured surgical patients.

Since the discovery and publication of the molecular structure of nucleic acids by Watson and Crick in 1954, the genetic basis for many conditions has been determined; however, misconceptions remain regarding the role of genetics and genomics in clinical medicine.³ Despite the commonly held notion that genetics had little influence on clinical medicine in the past, genetics has, in fact, played an important role in understanding disease, but only for a small number of conditions and patients. As a result of these, we have entered a period of tremendous growth in our knowledge of genomics that will eventually influence care for all patients.¹ In order for clinicians to understand and participate in these advances, we must become “literate” in the language of genomic medicine. Box 53-1 includes some important definitions of genetic concepts for clinicians, some of which will be more completely developed below.

Much is known about the human genome, including the fact that the minority of the 3 gigabases of DNA sequence codes for proteins. It is estimated that only 2% of our DNA sequence includes the codes for approximately 20,000 protein-coding genes. The function of the remaining 98% of DNA is perhaps the most fascinating aspect of genomics. Figure 53-1 illustrates the structure of a typical gene. The 5′ control region, often termed the “promoter,” includes DNA sequences that recognize and bind to proteins called transcription factors, whose function is to modify gene expression by controlling transcription. The “start codon” is a series of nucleotides that are recognized by the transcriptional machinery, which initiates the generation of messenger RNA (mRNA) from DNA. Not all of this mRNA sequence encodes for protein. Exons are the regions of DNA that are transcribed into RNA to make amino acids. In most genes, multiple exons are separated by introns, which are removed from mRNA prior to translation into protein. The end of transcription is signaled by a series of nucleotides at the end of the coding sequence, referred to as a “stop codon.” The DNA sequence after this stop codon, termed the 3′ control region, can influence the rate of gene transcription and may affect the stability of the mRNA sequence and its subsequent translation into protein, also.

Despite our limited knowledge of the function of much of the genome, our knowledge of the genetic basis for disease is extensive. Basic research and clinical observation have elucidated the inheritance of single gene, Mendelian disorders (transmitted according to Mendel’s laws of inheritance). Most of these are uncommon and, taken together, the most prevalent (eg, cystic fibrosis and hemochromatosis), affect no more than one in several hundred people; however, when the genetic variant is present, its effect on individual patients is substantial. Furthermore, understanding the mechanisms underlying many monogenic disorders has provided pathophysiological information about related, more common disorders. For instance, we have learned a great deal about the pathophysiology of cardiovascular disease from discoveries related to familial hypercholesterolemia, a rare genetic disorder leading to premature atherosclerosis.

The most common type of DNA sequence variation is single base substitutions termed single nucleotide polymorphisms (SNPs). As naturally occurring, SNPs have emerged as important genetic markers for studying multifactorial diseases.⁴ Polymorphisms occur in all individuals and, by strict definition, SNPs exist with a frequency of greater than 1%.⁵ Therefore, the term SNP does not include numerous other single base substitutions in which the least common allele is present at a frequency of less than equal to 1% (such as “personal mutations” that may be limited to one family), nor does the term encompass other variations such as insertion/deletion polymorphisms. Importantly, SNPs should be distinguished from disease “causing” mutations, which are generally much less common, but have higher penetrance (eg, sickle cell anemia). SNPs typically do not cause disease, but, in aggregate, may influence the risk for developing a disease (eg, diabetes mellitus, asthma) or the outcome from a disease or condition (eg, death from sepsis, rate of atherosclerosis in recipients of cardiac transplants).^6,7,8 SNPs that exist in mRNA-coding regions (exons) of DNA can lead to amino acid substitutions (termed a missense mutation) and, therefore, may change the structure and function of the resultant protein. This type of variant potentially has the most profound impact on protein function; however, this type of SNP is the least common.⁹ SNPs in the regulatory (promoter) region of a gene may influence (increase or, more often, decrease) transcription of that gene, and may influence the amount of protein available.¹⁰ Yet other SNPs may not directly alter protein abundance or function, but may be important markers for other (unidentified) functional variants—a concept known as linkage.⁹ Similarly, haplotypes can add complexity to this concept. A haplotype is a group of genes that are commonly inherited together, for instance, a group of SNPs on the same chromosome. Within a haplotype, a nonfunctional SNP may mark the presence of one or a group of other polymorphisms that directly alter a protein either in amount or function.

The analysis of SNPs has been facilitated by the two related following developments: (1) the establishment of large data repositories of SNPs and (2) the availability of relatively affordable “high-throughput” methods for genotyping. Recent techniques have identified at least 10 million SNPs interspersed throughout the human genome, at a frequency of one SNP per ~300 basepairs.¹¹ Their role in critical illness, both as risk factors and in determining treatment response, has been investigated for several candidate genes.¹² It is hoped that these studies will contribute to the understanding of the biology of critical illness and toward characterizing individual patient risk, treatment response and outcome.¹³