Health Sciences Graduate Program, Health Sciences Center, State University of Londrina, Av. Robert Koch, Londrina, PR, 60 86035-380, Brazil.
Department of Psychiatry, Chulalongkorn University, Bangkok, Thailand.
Mol Neurobiol. 2019 Sep;56(9):6626-6644. doi: 10.1007/s12035-019-1552-z. Epub 2019 Mar 25.
Although, staging models gained momentum to stage define affective disorders, no attempts were made to construct mathematical staging models using clinical and biomarker data in patients with major depression and bipolar disorder. The aims of this study were to use clinical and biomarker data to construct statistically derived staging models, which are associated with early lifetime traumata (ELTs), affective phenomenology, and biomarkers. In the current study, 172 subjects participated, 105 with affective disorders (both bipolar and unipolar) and 67 controls. Staging scores were computed by extracting latent vectors (LVs) from clinical data including ELTs, recurring flare ups and suicidal behaviors, outcome data such as disabilities and health-related quality of life (HR-QoL), and paraoxonase (PON)1 actvities and nitro-oxidative stress biomarkers. Recurrence of episodes and suicidal behaviors could reliably be combined into a LV with adequate composite reliability (the "recurrence LV"), which was associated with female sex, the combined effects of multiple ELTs, disabilities, HR-QoL, and impairments in cognitive tests. All those factors could be combined into a reliable "ELT-staging LV" which was significantly associated with nitro-oxidative stress biomarkers. A reliable LV could be extracted from serum PON1 activities, recurrent flare ups, disabilities, and HR-QoL. Our ELT-staging index scores the severity of a relevant affective dimension, shared by both major depression and bipolar disorder, namely the trajectory from ELTs, a relapsing course, and suicidal behaviors to progressive disabilities. Patients were classified into three stages, namely an early stage, a relapse-regression stage, and a suicidal-regression stage. Lowered lipid-associated antioxidant defenses may be a drug target to prevent the transition from the early to the later regression stages.
虽然分期模型已经取得了进展，用于对情感障碍进行分期定义，但在重度抑郁症和双相情感障碍患者中，尚未尝试使用临床和生物标志物数据构建数学分期模型。本研究旨在使用临床和生物标志物数据构建与早期生命创伤（ELTs）、情感表现和生物标志物相关的统计衍生分期模型。在当前研究中，共有 172 名受试者参与，其中 105 名患有情感障碍（包括双相和单相），67 名作为对照。分期评分是通过从包括 ELTs、反复发作和自杀行为在内的临床数据中提取潜在向量（LVs）来计算的，还包括结局数据，如残疾和与健康相关的生活质量（HR-QoL），以及对氧磷酶（PON）1 活性和硝基氧化应激生物标志物。发作的复发和自杀行为可以可靠地组合成一个具有足够综合可靠性的 LV（“复发 LV”），该 LV 与女性、多种 ELTs 的综合效应、残疾、HR-QoL 以及认知测试受损有关。所有这些因素都可以组合成一个可靠的“ELT-分期 LV”，与硝基氧化应激生物标志物显著相关。可以从血清 PON1 活性、反复发作、残疾和 HR-QoL 中提取出可靠的 LV。我们的 ELT 分期指数评估了由 ELTs、反复发作和自杀行为导致的残疾的严重程度，这是一种共同存在于重度抑郁症和双相情感障碍中的相关情感维度。患者被分为三个阶段，即早期阶段、复发-缓解阶段和自杀-缓解阶段。降低与脂质相关的抗氧化防御可能是预防从早期向后期缓解阶段转变的药物靶点。
