Department of Psychiatry, Oregon Health & Science University, Portland, Oregon.
Department of Psychiatry, Oregon Health & Science University, Portland, Oregon.
Biol Psychiatry Cogn Neurosci Neuroimaging. 2020 Aug;5(8):726-737. doi: 10.1016/j.bpsc.2020.02.005. Epub 2020 Feb 24.
Attention-deficit/hyperactivity disorder (ADHD) is among the many syndromes in the psychiatric nosology for which etiological signal and clinical prediction are weak. Reducing phenotypic and mechanistic heterogeneity should be useful to arrive at stronger etiological and clinical prediction signals. We discuss key conceptual and methodological issues, highlighting the role of dimensional features aligned with Research Domain Criteria and cognitive, personality, and temperament theory as well as neurobiology. We describe several avenues of work in this area, utilizing different statistical, computational, and machine learning approaches to resolve heterogeneity in ADHD. We offer methodological and conceptual recommendations. Methodologically, we propose that an integrated approach utilizing theory and advanced computational logic to address targeted questions, with consideration of developmental context, can render the heterogeneity problem tractable for ADHD. Conceptually, we conclude that the field is on the cusp of justifying an emotionally dysregulated subprofile in ADHD that may be useful for clinical prediction and treatment testing. Cognitive profiles, while more nascent, may be useful for clinical prediction and treatment assignment in different ways depending on developmental stage. Targeting these psychological profiles for neurobiological and etiological study to capture different pathophysiological routes remains a near-term opportunity. Subtypes are likely to be multifactorial, cut across multiple dimensions, and depend on the research or clinical outcomes of interest for their ultimate selection. In this context parallel profiles based on cognition, emotion, and specific neural signatures appear to be on the horizon, each with somewhat different utilities. Efforts to integrate such cross-cutting profiles within a conceptual dysregulation framework are well underway.
注意缺陷多动障碍(ADHD)是精神病学分类中众多综合征之一,其病因信号和临床预测都很薄弱。减少表型和机制的异质性应该有助于产生更强的病因和临床预测信号。我们讨论了关键的概念和方法问题,强调了与研究领域标准以及认知、人格和气质理论以及神经生物学相一致的维度特征的作用。我们描述了该领域的几个工作途径,利用不同的统计、计算和机器学习方法来解决 ADHD 中的异质性问题。我们提出了方法和概念上的建议。从方法上讲,我们建议采用一种综合方法,利用理论和先进的计算逻辑来解决有针对性的问题,并考虑到发展背景,这可以使 ADHD 的异质性问题变得易于处理。从概念上讲,我们得出的结论是,该领域即将证明 ADHD 中存在情绪失调亚组是合理的,这对于临床预测和治疗测试可能是有用的。认知特征虽然还处于萌芽阶段,但根据发育阶段的不同,可能在临床预测和治疗分配方面具有不同的用途。针对这些心理特征进行神经生物学和病因学研究,以捕捉不同的病理生理途径,仍然是近期的机会。亚型可能是多因素的,跨越多个维度,并取决于研究或临床感兴趣的结果,最终选择这些亚型。在这种情况下,基于认知、情感和特定神经特征的平行特征似乎即将出现,每种特征都有不同的用途。将这些交叉特征整合到概念失调框架中的努力正在进行中。