Abstract
BackgroundIncreasing genetic variants associated with sepsis have been identified by candidate-gene and genome-wide association studies, but single variants conferred minimal alterations in risk prediction. Our aim is to evaluate whether a weighted genetic risk score (wGRS) that aggregates information from multiple variants could improve risk discrimination of traumatic sepsis.MethodsSixty-four genetic variants potential relating to sepsis were genotyped in Chinese trauma cohort. Genetic variants with mean decrease accuracy (MDA) > 1.0 by random forest algorithms were selected to construct the multilocus wGRS. The area under the curve (AUC) and net reclassification improvement (NRI) were adopted to evaluate the discriminatory and reclassification ability of weighted genetic risk score (wGRS).ResultsSeventeen variants were extracted to construct the wGRS in 883 trauma patients. The wGRS was significantly associated with sepsis after trauma (OR = 2.19, 95% CI = 1.53–3.15, P = 2.01 × 10–5) after being adjusted by age, sex, and ISS. Patients with higher wGRS have an increasing incidence of traumatic sepsis (Ptrend = 6.81 × 10–8), higher SOFA (Ptrend = 5.00 × 10–3), and APACHE II score (Ptrend = 1.00 × 10–3). The AUC of the risk prediction model incorporating wGRS into the clinical variables was 0.768 (95% CI = 0.739–0.796), with an increase of 3.40% (P = 8.00 × 10–4) vs. clinical factor-only model. Furthermore, the NRI increased 25.18% (95% CI = 17.84–32.51%) (P = 6.00 × 10–5).ConclusionOur finding indicated that genetic variants could enhance the predictive power of the risk model for sepsis and highlighted the application among trauma patients, suggesting that the sepsis risk assessment model will be a promising screening and prediction tool for the high-risk population.
Highlights
Trauma is the fourth leading cause of death around the world
Our results demonstrated that when incorporating weighted genetic risk score (wGRS) into the injury severity score (ISS), the areas under the curve (AUC) of the prediction model increased to 0.768 (95%CI = 0.739– 0.796), with an increase of 3.40% (P = 8.00 × 10−4) (Figure 3B)
We considered Net reclassification improvement (NRI) to estimate the reclassification of the prediction model when wGRS was included
Summary
Trauma is the fourth leading cause of death around the world. Despite advances in clinical management of trauma patients, major trauma results in approximately 15% of disabilities and 10% of deaths (Lord et al, 2014). Sepsis is one of the most serious complications post major trauma, which might result in progressive dysfunction of vital organs (Park et al, 2016). In recent years, increasing numbers of sepsis-predisposing variants have been identified by candidate gene and genome-wide association studies (GWAS) (Villar et al, 2004; Rautanen et al, 2015). Rs4919510 in MIR608 and rs2232618 in the coding region of the LBP gene were both functional variants and conferred susceptibility to sepsis after trauma (Zeng et al, 2012; Zhang et al, 2015). Delineating genetic heterogeneity for sepsis might contribute to the diagnostic approaches and therapeutic trials among trauma patients. Increasing genetic variants associated with sepsis have been identified by candidate-gene and genome-wide association studies, but single variants conferred minimal alterations in risk prediction. Our aim is to evaluate whether a weighted genetic risk score (wGRS) that aggregates information from multiple variants could improve risk discrimination of traumatic sepsis
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