Predicting PTSD using the New York Risk Score with genotype data: potential clinical and research opportunities.

ABSTRACT: BACKGROUND:We previously developed a post-traumatic stress disorder (PTSD) screening instrument, ie, the New York PTSD Risk Score (NYPRS), that was effective in predicting PTSD. In the present study, we assessed a version of this risk score that also included genetic information. METHODS:Utilizing diagnostic testing methods, we hierarchically examined different prediction variables identified in previous NYPRS research, including genetic risk-allele information, to assess lifetime and current PTSD status among a population of trauma-exposed adults. RESULTS:We found that, in predicting lifetime PTSD, the area under the receiver operating characteristic curve (AUC) for the Primary Care PTSD Screen alone was 0.865. When we added psychosocial predictors from the original NYPRS to the model, including depression, sleep disturbance, and a measure of health care access, the AUC increased to 0.902, which was a significant improvement (P = 0.0021). When genetic information was added in the form of a count of PTSD risk alleles located within FKBP5, COMT, CHRNA5, and CRHR1 genetic loci (coded 0-6), the AUC increased to 0.920, which was also a significant improvement (P = 0.0178). The results for current PTSD were similar. In the final model for current PTSD with the psychosocial risk factors included, genotype resulted in a prediction weight of 17 for each risk allele present, indicating that a person with six risk alleles or more would receive a PTSD risk score of 17 × 6 = 102, the highest risk score for any of the predictors studied. CONCLUSION:Genetic information added to the NYPRS helped improve the accuracy of prediction results for a screening instrument that already had high AUC test results. This improvement was achieved by increasing PTSD prediction specificity. Further research validation is advised.

SUBMITTER: Boscarino JA 

PROVIDER: S-EPMC3666578 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature