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超越谱系:通过多模态数据整合对自闭症谱系障碍进行亚型特异性分子洞察。

Beyond the Spectrum: Subtype-Specific Molecular Insights into Autism Spectrum Disorder Via Multimodal Data Integration.

作者信息

Zahiri Javad, Mirzaie Mehdi, Duan Kuaikuai, Xiao Yaqiong, Aamodt Caitlin, Yang Xiaotong, Nazari Sanaz, Andreason Charlene, Lopez Linda, Barnes Cynthia Carter, Arias Steven, Nalabolu Srinivasa, Garmire Lana, Wang Tianyun, Hoekzema Kendra, Eichler Evan E, Pierce Karen, Lewis Nathan E, Courchesne Eric

机构信息

Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA.

Translational Neuroscience, Department of Pharmacology, Faculty of Medicine and Helsinki Institute of Life Science, 00014 University of Helsinki, Finland.

出版信息

medRxiv. 2024 Sep 23:2024.09.17.24313857. doi: 10.1101/2024.09.17.24313857.

Abstract

Some toddlers with autism spectrum disorder (ASD) have mild social symptoms and developmental improvement in skills, but for others, symptoms and abilities are moderately or even severely affected. Those with profound autism have the most severe social, language, and cognitive symptoms and are at the greatest risk of having a poor developmental outcome. The little that is known about the underlying biology of this important profound autism subtype, points clearly to embryonic dysregulation of proliferation, differentiation and neurogenesis. Because it is essential to gain foundational knowledge of the molecular biology associated with profound, moderate, and mild autism clinical subtypes, we used well-validated, data-driven patient subtyping methods to integrate clinical and molecular data at 1 to 3 years of age in a cohort of 363 ASD and controls representative of the general pediatric population in San Diego County. Clinical data were diagnostic, language, cognitive and adaptive ability scores. Molecular measures were 50 MSigDB Hallmark gene pathway activity scores derived from RNAseq gene expression. Subtyping identified four ASD, typical and mixed diagnostic clusters. 93% of subjects in one cluster were profound autism and 93% in a different cluster were control toddlers; a third cluster was 76% moderate ability ASD; and the last cluster was a mix of mild ASD and control toddlers. Among the four clusters, the profound autism subtype had the most severe social symptoms, language, cognitive, adaptive, social attention eye tracking, social fMRI activation, and age-related decline in abilities, while mild autism toddlers mixed within typical and delayed clusters had mild social symptoms, and neurotypical language, cognitive and adaptive scores that improved with age compared with profound and moderate autism toddlers in other clusters. In profound autism, 7 subtype- dysregulated gene pathways were found; they control embryonic proliferation, differentiation, neurogenesis, and DNA repair. To find subtype- dysregulated pathways, we compared all ASD vs TD and found 17 ASD subtype- dysregulated pathways. These pathways showed a severity gradient with the greatest dysregulation in profound and least in mild. Collectively, results raise the new hypothesis that the continuum of ASD heterogeneity is moderated by subtype- pathways and the distinctive nature of profound autism is driven by the differentially added profound subtype-.

摘要

一些患有自闭症谱系障碍(ASD)的幼儿有轻微的社交症状且技能发育有所改善,但对另一些幼儿来说,症状和能力受到中度甚至严重影响。患有重度自闭症的幼儿有最严重的社交、语言和认知症状,且发育不良的风险最大。关于这种重要的重度自闭症亚型的潜在生物学机制,目前所知甚少,但明确指向胚胎期增殖、分化和神经发生的失调。由于获取与重度、中度和轻度自闭症临床亚型相关的分子生物学基础知识至关重要,我们使用经过充分验证的数据驱动患者亚型分类方法,在一个由363名自闭症谱系障碍患者和对照组组成的队列中整合了1至3岁时的临床和分子数据,这些患者和对照组代表了圣地亚哥县的普通儿科人群。临床数据包括诊断、语言、认知和适应能力得分。分子测量指标是从RNA测序基因表达中得出的50个MSigDB标志性基因通路活性得分。亚型分类确定了四个自闭症谱系障碍、典型和混合诊断集群。一个集群中93%的受试者是重度自闭症患者,另一个不同集群中93%的受试者是对照幼儿;第三个集群中76%是中度能力的自闭症谱系障碍患者;最后一个集群是轻度自闭症谱系障碍患者和对照幼儿的混合。在这四个集群中,重度自闭症亚型有最严重的社交症状、语言、认知、适应、社交注意力眼动追踪、社交功能磁共振成像激活以及与年龄相关的能力下降,而混合在典型和发育迟缓集群中的轻度自闭症幼儿有轻微的社交症状,其神经典型语言、认知和适应得分随年龄增长而改善,与其他集群中的重度和中度自闭症幼儿相比情况较好。在重度自闭症中,发现了7条亚型失调的基因通路;它们控制胚胎增殖、分化、神经发生和DNA修复。为了找到亚型失调的通路,我们比较了所有自闭症谱系障碍患者与发育正常者,发现了17条自闭症谱系障碍亚型失调的通路。这些通路呈现出严重程度梯度,在重度自闭症中失调最严重,在轻度自闭症中最少。总体而言,研究结果提出了一个新假设,即自闭症谱系障碍异质性的连续体由亚型通路调节,重度自闭症的独特性质由差异添加的重度亚型驱动。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc98/11469458/1ae36cc2e4c3/nihpp-2024.09.17.24313857v3-f0001.jpg

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