Sex/gender differences in neurology and psychiatry: Autism.

Sex/gender differences in neurology and psychiatry: Autism.
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DOI:
10.1016/b978-0-444-64123-6.00020-5
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发表时间:
2020-01-01
影响因子:
--
通讯作者:
Lai, Meng-Chuan
Lai, Meng-Chuan
中科院分区:
其他
文献类型:
--
作者:
Ruigrok, Amber N V;Lai, Meng-Chuan

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孤独症是一种异质性的早发性神经发育状况,男性比女性更普遍。由于自闭症谱系具有高度的表型、神经生物学、发育和病因学异质性,最近的研究项目越来越多地探索性和性别相关因素是否可以成为澄清自闭症异质性的有用标记,并致力于个性化的治疗方法干预和支持。在本章中,我们总结了最近的临床和神经科学研究解决性/性别的影响,自闭症和探讨如何性别/性别为基础的调查揭示了类似或不同的潜在的神经发育机制的自闭症的性别/性别。我们回顾了可能有助于解释与自闭症相关的一些潜在的性相关生物学机制的证据,包括遗传学和产前环境中性类固醇激素的影响。我们的结论是,目前的研究指向共存的定量和,也许更明显,定性的性/性别调制的影响,在自闭症的多个神经生物学方面。然而,在自闭症谱系内的许多亚群中,仍然缺乏特定神经生物学表现和性别/性别知情机制的趋同研究结果。未来的研究应该使用大数据方法和新的分层方法来分解自闭症中与性别相关的异质性,并致力于个性化,性别/性别信息干预和支持自闭症患者。
Autism is a heterogenous set of early-onset neurodevelopmental conditions that are more prevalent in males than in females. Due to the high phenotypic, neurobiological, developmental, and etiological heterogeneity in the autism spectrum, recent research programs are increasingly exploring whether sex- and gender-related factors could be helpful markers to clarify the heterogeneity in autism and work toward a personalized approach to intervention and support. In this chapter, we summarize recent clinical and neuroscientific research addressing sex/gender influences in autism and explore how sex/gender-based investigations shed light on similar or different underlying neurodevelopmental mechanisms of autism by sex/gender. We review evidence that may help to explain some of the underlying sex-related biological mechanisms associated with autism, including genetics and the effects of sex steroid hormones in the prenatal environment. We conclude that current research points toward coexisting quantitative and, perhaps more evidently, qualitative sex/gender-modulation effects in autism across multiple neurobiological aspects. However, converging findings of specific neurobiological presentations and sex/gender-informed mechanisms cutting across the many subgroups within the autism spectrum are still lacking. Future research should use big data approaches and new stratification methods to decompose sex/gender-related heterogeneity in autism and work toward personalized, sex/gender-informed intervention and support for autistic people.