Multi-omic biomarker identification and validation for diagnosing warzone-related post-traumatic stress disorder.
Multi-omic biomarker identification and validation for diagnosing warzone-related post-traumatic stress disorder.
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DOI：
10.1038/s41380-019-0496-z
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发表时间：
2020-12
影响因子：
11
通讯作者：
Marmar C
中科院分区：
文献类型：
--
作者：
Dean KR;Hammamieh R;Mellon SH;Abu-Amara D;Flory JD;Guffanti G;Wang K;Daigle BJ Jr;Gautam A;Lee I;Yang R;Almli LM;Bersani FS;Chakraborty N;Donohue D;Kerley K;Kim TK;Laska E;Young Lee M;Lindqvist D;Lori A;Lu L;Misganaw B;Muhie S;Newman J;Price ND;Qin S;Reus VI;Siegel C;Somvanshi PR;Thakur GS;Zhou Y;PTSD Systems Biology Consortium;Hood L;Ressler KJ;Wolkowitz OM;Yehuda R;Jett M;Doyle FJ 3rd;Marmar C
创伤后应激障碍（PTSD）影响许多退伍军人和现役士兵，但由于自我披露症状的偏见，军人群体中的耻辱以及识别风险人群的局限性，诊断可能存在问题。先前的研究表明，PTSD可能是一种全身性疾病，不仅影响大脑，而且影响整个身体。因此，疾病信号可能跨越多个生物学领域，包括基因、蛋白质、细胞、组织和生物体水平的生理变化。这些信号的识别可以帮助诊断，治疗决策和风险评估。在寻找PTSD诊断生物标志物的过程中，我们从三组男性退伍军人中确定了超过一百万个分子，细胞，生理和临床特征。在83例warzone相关的PTSD病例和82例warzone暴露对照的发现队列中，我们确定了一组343个候选生物标志物。这些候选生物标志物是从综合方法中选择的，使用（1）数据驱动方法，包括具有递归特征消除的支持向量机和其他标准或已发布的方法，以及（2）假设驱动方法，使用之前的多基因风险遗传研究，或其他PTSD相关文献。在重新评估了约30%的参与者后，我们根据他们的表现和跟踪表型随时间变化的能力，将这组标记物从343个改进为28个。在一个独立的队列（26例病例，26例对照）中验证了28个特征的最终诊断面板，具有良好的性能（AUC = 0.80，81%的准确性，85%的灵敏度和77%的特异性）。这种多样性的诊断小组的识别和验证代表了一种强大而新颖的方法，以提高准确性，减少诊断与战斗有关的创伤后应激障碍的偏见。
Post-traumatic stress disorder (PTSD) impacts many veterans and active duty soldiers, but diagnosis can be problematic due to biases in self-disclosure of symptoms, stigma within military populations, and limitations identifying those at risk. Prior studies suggest that PTSD may be a systemic illness, affecting not just the brain, but the entire body. Therefore, disease signals likely span multiple biological domains, including genes, proteins, cells, tissues, and organism-level physiological changes. Identification of these signals could aid in diagnostics, treatment decision-making, and risk evaluation. In the search for PTSD diagnostic biomarkers, we ascertained over one million molecular, cellular, physiological, and clinical features from three cohorts of male veterans. In a discovery cohort of 83 warzone-related PTSD cases and 82 warzone-exposed controls, we identified a set of 343 candidate biomarkers. These candidate biomarkers were selected from an integrated approach using (1) data-driven methods, including Support Vector Machine with Recursive Feature Elimination and other standard or published methodologies, and (2) hypothesis-driven approaches, using previous genetic studies for polygenic risk, or other PTSD-related literature. After reassessment of ~30% of these participants, we refined this set of markers from 343 to 28, based on their performance and ability to track changes in phenotype over time. The final diagnostic panel of 28 features was validated in an independent cohort (26 cases, 26 controls) with good performance (AUC = 0.80, 81% accuracy, 85% sensitivity, and 77% specificity). The identification and validation of this diverse diagnostic panel represents a powerful and novel approach to improve accuracy and reduce bias in diagnosing combat-related PTSD.
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影响因子：
6
作者：
Ghai V;Wu X;Bheda-Malge A;Argyropoulos CP;Bernardo JF;Orchard T;Galas D;Wang K
通讯作者：
Wang K
影响因子：
3.3
作者：
de Gonzalo-Calvo, David;Davalos, Alberto;Iglesias-Gutierrez, Eduardo
通讯作者：
Iglesias-Gutierrez, Eduardo
影响因子：
6.6
作者：
Ali-Sisto, Toni;Tolmunen, Tommi;Lehto, Soili M.
通讯作者：
Lehto, Soili M.
影响因子：
3.7
作者：
Blessing, Esther M.;Reus, Victor;Marmar, Charles R.
通讯作者：
Marmar, Charles R.
影响因子：
7.6
作者：
Breen, Michael S.;Tylee, Daniel S.;Glatt, Stephen J.
通讯作者：
Glatt, Stephen J.