Identification of ASD biomarkers is a key priority for understanding etiology, facilitating early diagnosis, monitoring developmental trajectories, and targeting treatment efforts. Efforts have included exploration of resting state encephalography (EEG), which has a variety of relevant neurodevelopmental correlates and can be collected with minimal burden. However, EEG biomarkers may not be equally valid across the autism spectrum, as ASD is strikingly heterogeneous and individual differences may moderate EEG-behavior associations. Biological sex is a particularly important potential moderator, as females with ASD appear to differ from males with ASD in important ways that may influence biomarker accuracy. We examined effects of biological sex, age, and ASD diagnosis on resting state EEG among a large, sex-balanced sample of youth with (N = 142, 43% female) and without (N = 138, 49% female) ASD collected across four research sites. Absolute power was extracted across five frequency bands and nine brain regions, and effects of sex, age, and diagnosis were analyzed using mixed-effects linear regression models. Exploratory partial correlations were computed to examine EEG-behavior associations in ASD, with emphasis on possible sex differences in associations. Decreased EEG power across multiple frequencies was associated with female sex and older age. Youth with ASD displayed decreased alpha power relative to peers without ASD, suggesting increased neural activation during rest. Associations between EEG and behavior varied by sex. Whereas power across various frequencies correlated with social skills, nonverbal IQ, and repetitive behavior for males with ASD, no such associations were observed for females with ASD. Research using EEG as a possible ASD biomarker must consider individual differences among participants, as these features influence baseline EEG measures and moderate associations between EEG and important behavioral outcomes. Failure to consider factors such as biological sex in such research risks defining biomarkers that misrepresent females with ASD, hindering understanding of the neurobiology, development, and intervention response of this important population.

中文翻译：

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ASD 青年的静息状态脑电图：年龄、性别和与表型的关系

识别 ASD 生物标志物是了解病因、促进早期诊断、监测发育轨迹和靶向治疗工作的关键优先事项。努力包括探索静息状态脑电图 (EEG)，它具有多种相关的神经发育相关性，可以以最小的负担收集。然而，EEG 生物标志物在自闭症谱系中可能并不同样有效，因为 ASD 具有显着的异质性，个体差异可能会调节 EEG 行为关联。生物性别是一个特别重要的潜在调节因素，因为患有 ASD 的女性似乎在可能影响生物标志物准确性的重要方面不同于患有 ASD 的男性。我们检查了生物学性别、年龄和 ASD 诊断对静息状态脑电图的影响，在一个大型、性别平衡的青年样本中（N = 142，43% 女性) 和没有 (N = 138, 49% 女性) ASD 在四个研究地点收集。在五个频带和九个大脑区域中提取绝对功率，并使用混合效应线性回归模型分析性别、年龄和诊断的影响。计算探索性偏相关以检查 ASD 中的 EEG 行为关联，重点是关联中可能存在的性别差异。跨多个频率的脑电图功率下降与女性和年龄较大有关。与没有 ASD 的同龄人相比，患有 ASD 的青年表现出降低的 alpha 功率，这表明在休息期间神经激活增加。脑电图与行为之间的关联因性别而异。鉴于不同频率的力量与 ASD 男性的社交技能、非语言智商和重复行为相关，对于患有 ASD 的女性，没有观察到这种关联。使用 EEG 作为可能的 ASD 生物标志物的研究必须考虑参与者之间的个体差异，因为这些特征会影响基线 EEG 测量以及 EEG 与重要行为结果之间的适度关联。在此类研究中未能考虑生物性别等因素可能会定义错误代表患有 ASD 的女性的生物标志物，从而阻碍对这一重要人群的神经生物学、发育和干预反应的理解。