We report evidence for a familial/genetic contribution to SSI. We have attempted to identify SSI6
cases using 3 sequentially defined sets of codes, each more inclusive than the last. It is clear that the phenotype description is critical, although we saw similar results for all 3 phenotypes analyzed. The GIF analysis for each of the 3 defined groups of patients with SSI shows that the average relatedness observed for cases was significantly higher than expected. Only the group of SSI patients defined with inclusion of prosthesis, but not catheter/infusion showed significant excess clustering for all relationships and also for distant relationships only, although the other two SSI phenotype groups had similar dGIF (borderline significant) results, and the GIF distributions in show excess distant relationships for all 3 phenotype groups. As the sample size of each group increased, more relationships were observed and a smoother overall distribution for cases was observed. The GIF analysis of the largest set of SSI cases support a genetic contribution to predisposition to infection following surgery, with an excess of relationships even beyond third cousins (genetic distance = 8).
The RR analysis for the 3 phenotype groups of SSI patients showed varying results as well. For the smallest phenotype group (n=350), no first- or second-degree relatives were observed among relatives of matched controls. In the largest phenotype group considered (n=1650), in which many more relatives were considered, all of the RR estimates were > 1.0 and the second- and third-degree RR estimates were significantly elevated. Again, these results support a shared genetic component to SSI predisposition.
One major limitation to this study is the use of ICD-9 codes to identify patients diagnosed with SSI. Physicians use variable codes to record SSI and surveillance for SSI is often inadequate16
. Patients may develop SSI after discharge. UUHSC participates in the National Surgical Quality Improvement Project and the aggressive surveillance required by the program may have improved capture of SSI for more recent years. Although it is likely our data understate the incidence of SSI, it is unlikely that infections are not captured in a way that would bias our results. The reduced sample size entailed by missed SSI may have limited our ability to identify significant results. Some patients may have been inaccurately coded as having SSI and the codes we used would have captured some patients who did not in fact have SSI. Again, it is unlikely that there was a bias in how these data were included and excluded that would have changed our results. Because we are using a Utah population resource for analysis, SSI patients whose genealogy data is not complete in the UPDB and individuals diagnosed with a SSI before UUHSC data availability are also censored. We do not anticipate that this censoring results in any bias as it applies equally to all individuals whether they are cases or controls. Within the context of the goal of our study, our data support the idea that evaluation of individuals within affected pedigrees to determine which genes contribute to susceptibility to SSI is likely to be a fruitful avenue of research.
Another limitation of our study is the inability to control for confounding factors such as diabetes, obesity, smoking, need for multiple operations, need for higher risk operations, malnutrition, cardiopulmonary dysfunction, and use of immunosuppressant drugs. Some of these confounders have or may have a genetic basis, which could contribute to our findings.
Although the use of ICD-9 codes is limitation of our study, the data are of sufficient quality to support further investigation into the genetics of SSI susceptibility. The etiology of increased predisposition to SSI demonstrated in this study is likely both genetic and environmental. Our study does not define the genes that increase SSI risk. Likely candidates for a predisposition to SSI include SNPs related to impaired inflammation. Genes related to inflammation that have known SNPs include TNF-alpha, IL-1, IL-6, IL-10, heat shock genes, and lipopolysaccharide binding protein.7,17
Certain alleles of these genes are associated with greater risk of sepsis and / or of death from sepsis. Sepsis and SSI are clearly different disease processes, but inflammation plays a major role in each, so it is reasonable to speculate that these SNPs are also pertinent to SSI. Another candidate gene is the phagosomal oxidase (phox), which converts oxygen to superoxide, and plays a key role in host defense18
. SNPs in phox cause Chronic Granulomatous Disease19
, a rare condition that manifests early in childhood and in which patients develop severe recurrent infections, often of the skin, because of the inability to generate superoxide. The genetics of these catastrophic mutations have been studied in detail, but other genetic variations in phox have not been evaluated. It is plausible that SNPs that only reduce superoxide production may cause susceptibility to SSI without overt disease. Other genetic variants could predispose to disorders that require surgery or a propensity towards obesity, diabetes, connective tissue disorders, or other risk factors for SSI.
Our data support a genetic contribution to susceptibility to SSI. The next step is to define which genes are involved. Using the UPDB and with appropriate IRB approval we plan to identify, recruit, and obtain blood samples from members of the high-risk pedigrees identified in these analyses. This will allow us to genotype the most informative pedigrees and use linkage analysis as well as sequencing to identify candidate genes that may predispose patients to SSI and other infections.