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利用纽约风险评分和基因型数据预测 PTSD:潜在的临床和研究机会。

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

机构信息

Center for Health Research, Geisinger Clinic, Danville, PA, USA ; Department of Psychiatry, Temple University School of Medicine, Philadelphia, PA, USA.

出版信息

Neuropsychiatr Dis Treat. 2013;9:517-27. doi: 10.2147/NDT.S42422. Epub 2013 Apr 15.

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.

摘要

背景

我们之前开发了一种创伤后应激障碍(PTSD)筛查工具,即纽约 PTSD 风险评分(NYPRS),该工具在预测 PTSD 方面非常有效。在本研究中,我们评估了该风险评分的一个版本,该版本还包括遗传信息。

方法

利用诊断测试方法,我们分层检查了之前 NYPRS 研究中确定的不同预测变量,包括遗传风险等位基因信息,以评估创伤后暴露的成年人群中的终生和当前 PTSD 状况。

结果

我们发现,在预测终生 PTSD 时,单独使用初级保健 PTSD 筛查量表的受试者工作特征曲线下面积(AUC)为 0.865。当我们将原始 NYPRS 中的心理社会预测因素(包括抑郁、睡眠障碍和医疗保健获取措施)添加到模型中时,AUC 增加到 0.902,这是显著的改善(P=0.0021)。当以 FKBP5、COMT、CHRNA5 和 CRHR1 基因座内 PTSD 风险等位基因(编码 0-6)计数的形式添加遗传信息时,AUC 增加到 0.920,这也是显著的改善(P=0.0178)。当前 PTSD 的结果相似。在包含心理社会风险因素的当前 PTSD 的最终模型中,基因型导致每个存在的风险等位基因的预测权重为 17,这表明一个人如果存在 6 个或更多的风险等位基因,那么他的 PTSD 风险评分将为 17×6=102,这是研究中任何预测因素的最高风险评分。

结论

NYPRS 中添加的遗传信息有助于提高已经具有高 AUC 测试结果的筛查工具的预测结果的准确性。这种改进是通过提高 PTSD 预测的特异性来实现的。建议进一步进行研究验证。

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