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利用气质维度对注意力缺陷/多动障碍进行亚型分类:迈向基于生物学的疾病分类标准。

Subtyping attention-deficit/hyperactivity disorder using temperament dimensions: toward biologically based nosologic criteria.

作者信息

Karalunas Sarah L, Fair Damien, Musser Erica D, Aykes Kamari, Iyer Swathi P, Nigg Joel T

机构信息

Division of Psychology, Department of Psychiatry, Oregon Health and Science University, Portland.

Division of Psychology, Department of Psychiatry, Oregon Health and Science University, Portland2Department of Behavioral Neuroscience, Oregon Health and Science University, Portland3Advanced Imaging Research Center, Oregon Health and Science University.

出版信息

JAMA Psychiatry. 2014 Sep;71(9):1015-24. doi: 10.1001/jamapsychiatry.2014.763.

Abstract

IMPORTANCE

Psychiatric nosology is limited by behavioral and biological heterogeneity within existing disorder categories. The imprecise nature of current nosologic distinctions limits both mechanistic understanding and clinical prediction. We demonstrate an approach consistent with the National Institute of Mental Health Research Domain Criteria initiative to identify superior, neurobiologically valid subgroups with better predictive capacity than existing psychiatric categories for childhood attention-deficit/hyperactivity disorder (ADHD).

OBJECTIVE

To refine subtyping of childhood ADHD by using biologically based behavioral dimensions (i.e., temperament), novel classification algorithms, and multiple external validators.

DESIGN, SETTING, AND PARTICIPANTS: A total of 437 clinically well-characterized, community-recruited children, with and without ADHD, participated in an ongoing longitudinal study. Baseline data were used to classify children into subgroups based on temperament dimensions and examine external validators including physiological and magnetic resonance imaging measures. One-year longitudinal follow-up data are reported for a subgroup of the ADHD sample to address stability and clinical prediction.

MAIN OUTCOMES AND MEASURES

Parent/guardian ratings of children on a measure of temperament were used as input features in novel community detection analyses to identify subgroups within the sample. Groups were validated using 3 widely accepted external validators: peripheral physiological characteristics (cardiac measures of respiratory sinus arrhythmia and pre-ejection period), central nervous system functioning (via resting-state functional connectivity magnetic resonance imaging), and clinical outcomes (at 1-year longitudinal follow-up).

RESULTS

The community detection algorithm suggested 3 novel types of ADHD, labeled as mild (normative emotion regulation), surgent (extreme levels of positive approach-motivation), and irritable (extreme levels of negative emotionality, anger, and poor soothability). Types were independent of existing clinical demarcations including DSM-5 presentations or symptom severity. These types showed stability over time and were distinguished by unique patterns of cardiac physiological response, resting-state functional brain connectivity, and clinical outcomes 1 year later.

CONCLUSIONS AND RELEVANCE

Results suggest that a biologically informed temperament-based typology, developed with a discovery-based community detection algorithm, provides a superior description of heterogeneity in the ADHD population than does any current clinical nosologic criteria. This demonstration sets the stage for more aggressive attempts at a tractable, biologically based nosology.

摘要

重要性

精神疾病分类学受到现有疾病类别中行为和生物学异质性的限制。当前分类学区分的不精确性限制了机制理解和临床预测。我们展示了一种与美国国立精神卫生研究所研究领域标准计划相一致的方法,以识别比现有儿童注意力缺陷多动障碍(ADHD)精神科类别具有更好预测能力的、神经生物学上有效的优势亚组。

目的

通过使用基于生物学的行为维度(即气质)、新型分类算法和多个外部验证指标来完善儿童ADHD的亚型分类。

设计、背景和参与者:共有437名经临床充分表征、从社区招募的有或无ADHD的儿童参与了一项正在进行的纵向研究。基线数据用于根据气质维度将儿童分类为亚组,并检查包括生理和磁共振成像测量在内的外部验证指标。报告了ADHD样本亚组的一年纵向随访数据,以探讨稳定性和临床预测。

主要结局和指标

在新型社区检测分析中,将父母/监护人对儿童气质测量的评分用作输入特征,以识别样本中的亚组。使用3个广泛接受的外部验证指标对分组进行验证:外周生理特征(呼吸性窦性心律不齐和射血前期的心脏测量)、中枢神经系统功能(通过静息态功能连接磁共振成像)和临床结局(在一年纵向随访时)。

结果

社区检测算法提示了3种新型ADHD,分别标记为轻度(规范情绪调节型)、活跃型(积极趋近动机水平极高型)和易激惹型(消极情绪、愤怒和安抚性差水平极高型)。这些类型独立于现有的临床划分,包括《精神疾病诊断与统计手册》第5版的表现形式或症状严重程度。这些类型随时间表现出稳定性,并在一年后通过独特的心脏生理反应模式、静息态功能性脑连接和临床结局加以区分。

结论与意义

结果表明,通过基于发现的社区检测算法开发的基于生物学信息的气质类型学,比任何当前的临床分类标准能更好地描述ADHD人群的异质性。这一示范为在易于处理的、基于生物学的分类学方面进行更积极的尝试奠定了基础。

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