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本文引用的文献

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2
Facial expression recognition is linked to clinical and neurofunctional differences in autism.面部表情识别与自闭症的临床和神经功能差异有关。
Mol Autism. 2022 Nov 10;13(1):43. doi: 10.1186/s13229-022-00520-7.
3
From mechanisms to markers: novel noninvasive EEG proxy markers of the neural excitation and inhibition system in humans.从机制到标志物:人类神经兴奋和抑制系统的新型无创 EEG 代理标志物。
Transl Psychiatry. 2022 Nov 8;12(1):467. doi: 10.1038/s41398-022-02218-z.
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Neurodiversity and Early Autism.神经多样性与早期自闭症
JAMA Pediatr. 2022 Dec 1;176(12):1272-1273. doi: 10.1001/jamapediatrics.2022.4144.
5
Autism as emergent and transactional.自闭症是一种动态发展且相互影响的病症。
Front Psychiatry. 2022 Oct 7;13:988755. doi: 10.3389/fpsyt.2022.988755. eCollection 2022.
6
Advances in the identification and validation of autism biomarkers.自闭症生物标志物识别与验证的进展。
Nat Rev Drug Discov. 2022 Oct;21(10):697-698. doi: 10.1038/d41573-022-00141-y.
7
The Autism Biomarkers Consortium for Clinical Trials: Initial Evaluation of a Battery of Candidate EEG Biomarkers.自闭症临床试验生物标志物联盟:候选脑电图生物标志物组的初步评估。
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8
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9
A Data-Driven Approach in an Unbiased Sample Reveals Equivalent Sex Ratio of Autism Spectrum Disorder-Associated Impairment in Early Childhood.一项基于无偏样本的数据分析表明,自闭症谱系障碍相关的早期发育损伤在男女性别上的比例相当。
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10
Early life adversity shapes neural circuit function during sensitive postnatal developmental periods.早期生活逆境会在敏感的产后发育期间塑造神经回路功能。
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自闭症生物标志物发现的当前状况是否反映了精准医学中还原论的局限性?关于一种综合方法的建议,该方法考虑大脑、身体和社会环境之间的动态机制。

Does the current state of biomarker discovery in autism reflect the limits of reductionism in precision medicine? Suggestions for an integrative approach that considers dynamic mechanisms between brain, body, and the social environment.

作者信息

Loth Eva

机构信息

Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.

出版信息

Front Psychiatry. 2023 Feb 22;14:1085445. doi: 10.3389/fpsyt.2023.1085445. eCollection 2023.

DOI:10.3389/fpsyt.2023.1085445
PMID:36911126
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9992810/
Abstract

Over the past decade, precision medicine has become one of the most influential approaches in biomedical research to improve early detection, diagnosis, and prognosis of clinical conditions and develop mechanism-based therapies tailored to individual characteristics using biomarkers. This perspective article first reviews the origins and concept of precision medicine approaches to autism and summarises recent findings from the first "generation" of biomarker studies. Multi-disciplinary research initiatives created substantially larger, comprehensively characterised cohorts, shifted the focus from group-comparisons to individual variability and subgroups, increased methodological rigour and advanced analytic innovations. However, although several candidate markers with probabilistic value have been identified, separate efforts to divide autism by molecular, brain structural/functional or cognitive markers have not identified a validated diagnostic subgroup. Conversely, studies of specific monogenic subgroups revealed substantial variability in biology and behaviour. The second part discusses both conceptual and methodological factors in these findings. It is argued that the predominant reductionist approach, which seeks to parse complex issues into simpler, more tractable units, let us to neglect the interactions between brain and body, and divorce individuals from their social environment. The third part draws on insights from systems biology, developmental psychology and neurodiversity approaches to outline an integrative approach that considers the dynamic interaction between biological (brain, body) and social mechanisms (stress, stigma) to understanding the origins of autistic features in particular conditions and contexts. This requires 1) closer collaboration with autistic people to increase face validity of concepts and methodologies; (2) development of measures/technologies that enable repeat assessment of social and biological factors in different (naturalistic) conditions and contexts, (3) new analytic methods to study (simulate) these interactions (including emergent properties), and (4) cross-condition designs to understand which mechanisms are transdiagnostic or specific for particular autistic sub-populations. Tailored support may entail both creating more favourable conditions in the social environment and interventions for some autistic people to increase well-being.

摘要

在过去十年中,精准医学已成为生物医学研究中最具影响力的方法之一,旨在改善临床疾病的早期检测、诊断和预后,并利用生物标志物开发针对个体特征的基于机制的疗法。这篇观点文章首先回顾了自闭症精准医学方法的起源和概念,并总结了第一代生物标志物研究的最新发现。多学科研究计划创建了规模更大、特征更全面的队列,将重点从群体比较转向个体差异和亚组,提高了方法的严谨性并推进了分析创新。然而,尽管已经确定了几个具有概率价值的候选标志物,但通过分子、脑结构/功能或认知标志物对自闭症进行分类的单独努力尚未确定一个经过验证的诊断亚组。相反,对特定单基因亚组的研究揭示了生物学和行为方面的巨大差异。第二部分讨论了这些发现中的概念和方法学因素。有人认为,占主导地位的还原论方法试图将复杂问题分解为更简单、更易于处理的单元,这让我们忽视了大脑与身体之间的相互作用,并使个体与其社会环境脱节。第三部分借鉴系统生物学、发展心理学和神经多样性方法的见解,概述了一种综合方法,该方法考虑生物(大脑、身体)和社会机制(压力、污名)之间的动态相互作用,以理解特定条件和背景下自闭症特征的起源。这需要:(1)与自闭症患者更密切合作,以提高概念和方法的表面效度;(2)开发能够在不同(自然主义)条件和背景下重复评估社会和生物因素的测量方法/技术;(3)研究(模拟)这些相互作用(包括涌现特性)的新分析方法;(4)跨条件设计,以了解哪些机制是跨诊断的或特定于特定自闭症亚群体的。量身定制的支持可能既需要在社会环境中创造更有利的条件,也需要对一些自闭症患者进行干预以提高幸福感。