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

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-specific dysregulated gene pathways were found; they control embryonic proliferation, differentiation, neurogenesis, and DNA repair. To find subtype-common dysregulated pathways, we compared all ASD vs TD and found 17 ASD subtype-common dysregulated pathways. These common 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-common pathways and the distinctive nature of profound autism is driven by the differentially added profound subtype-specific embryonic pathways.

Embryonic origin of two ASD subtypes of social symptom severity: the larger the brain cortical organoid size, the more severe the social symptoms.

BACKGROUND: Social affective and communication symptoms are central to autism spectrum disorder (ASD), yet their severity differs across toddlers: Some toddlers with ASD display improving abilities across early ages and develop good social and language skills, while others with "profound" autism have persistently low social, language and cognitive skills and require lifelong care. The biological origins of these opposite ASD social severity subtypes and developmental trajectories are not known. METHODS: Because ASD involves early brain overgrowth and excess neurons, we measured size and growth in 4910 embryonic-stage brain cortical organoids (BCOs) from a total of 10 toddlers with ASD and 6 controls (averaging 196 individual BCOs measured/subject). In a 2021 batch, we measured BCOs from 10 ASD and 5 controls. In a 2022 batch, we  tested replicability of BCO size and growth effects by generating and measuring an independent batch of BCOs from 6 ASD and 4 control subjects. BCO size was analyzed within the context of our large, one-of-a-kind social symptom, social attention, social brain and social and language psychometric normative datasets ranging from N = 266 to N = 1902 toddlers. BCO growth rates were examined by measuring size changes between 1- and 2-months of organoid development. Neurogenesis markers at 2-months were examined at the cellular level. At the molecular level, we measured activity and expression of Ndel1; Ndel1 is a prime target for cell cycle-activated kinases; known to regulate cell cycle, proliferation, neurogenesis, and growth; and known to be involved in neuropsychiatric conditions. RESULTS: At the BCO level, analyses showed BCO size was significantly enlarged by 39% and 41% in ASD in the 2021 and 2022 batches. The larger the embryonic BCO size, the more severe the ASD social symptoms. Correlations between BCO size and social symptoms were r = 0.719 in the 2021 batch and r = 0. 873 in the replication 2022 batch. ASD BCOs grew at an accelerated rate nearly 3 times faster than controls. At the cell level, the two largest ASD BCOs had accelerated neurogenesis. At the molecular level, Ndel1 activity was highly correlated with the growth rate and size of BCOs. Two BCO subtypes were found in ASD toddlers: Those in one subtype had very enlarged BCO size with accelerated rate of growth and neurogenesis; a profound autism clinical phenotype displaying severe social symptoms, reduced social attention, reduced cognitive, very low language and social IQ; and substantially altered growth in specific cortical social, language and sensory regions. Those in a second subtype had milder BCO enlargement and milder social, attention, cognitive, language and cortical differences. LIMITATIONS: Larger samples of ASD toddler-derived BCO and clinical phenotypes may reveal additional ASD embryonic subtypes. CONCLUSIONS: By embryogenesis, the biological bases of two subtypes of ASD social and brain development-profound autism and mild autism-are already present and measurable and involve dysregulated cell proliferation and accelerated neurogenesis and growth. The larger the embryonic BCO size in ASD, the more severe the toddler's social symptoms and the more reduced the social attention, language ability, and IQ, and the more atypical the growth of social and language brain regions.

Single-cell A/B testing for cell-cell communication.

A new method developed by Francisco Quintana's group, systematic perturbation of encapsulated associated cells followed by sequencing (SPEAC-seq), applies a CRISPR screen to co-cultured interacting cells to identify the ligands mediating cell-cell communication. Using this approach, the authors discover the molecular basis of a microglia-astrocyte feedback loop that suppresses neuroinflammatory disease.

Inhibition of miR-128 Enhances Vocal Sequence Organization in Juvenile Songbirds.

The molecular mechanisms underlying learned vocal communication are not well characterized. This is a major barrier for developing treatments for conditions affecting social communication, such as autism spectrum disorder (ASD). Our group previously generated an activity-dependent gene expression network in the striatopallidal song control nucleus, Area X, in adult zebra finches to identify master regulators of learned vocal behavior. This dataset revealed that the two host genes for microRNA-128, ARPP21 and R3HDM1, are among the top genes whose expression correlates to how much birds sing. Here we examined whether miR-128 itself is behaviorally regulated in Area X and found that its levels decline with singing. We hypothesized that reducing miR-128 during the critical period for vocal plasticity would enhance vocal learning. To test this, we bilaterally injected an antisense miR-128 construct (AS miR-128) or a control scrambled sequence into Area X at post-hatch day 30 (30 d) using sibling-matched experimental and control pupils. The juveniles were then returned to their home cage and raised with their tutors. Strikingly, inhibition of miR-128 in young birds enhanced the organization of learned vocal sequences. Tutor and pupil stereotypy scores were positively correlated, though the correlation was stronger between tutors and control pupils compared to tutors and AS miR-128 pupils. This difference was driven by AS miR-128 pupils achieving higher stereotypy scores despite their tutors' lower syntax scores. AS miR-128 birds with tutors on the higher end of the stereotypy spectrum were more likely to produce songs with faster tempos relative to sibling controls. Our results suggest that low levels of miR-128 facilitate vocal sequence stereotypy. By analogy, reducing miR-128 could enhance the capacity to learn to speak in patients with non-verbal ASD. To our knowledge, this study is the first to directly link miR-128 to learned vocal communication and provides support for miR-128 as a potential therapeutic target for ASD.

Context-aware deconvolution of cell-cell communication with Tensor-cell2cell.

Cell interactions determine phenotypes, and intercellular communication is shaped by cellular contexts such as disease state, organismal life stage, and tissue microenvironment. Single-cell technologies measure the molecules mediating cell-cell communication, and emerging computational tools can exploit these data to decipher intercellular communication. However, current methods either disregard cellular context or rely on simple pairwise comparisons between samples, thus limiting the ability to decipher complex cell-cell communication across multiple time points, levels of disease severity, or spatial contexts. Here we present Tensor-cell2cell, an unsupervised method using tensor decomposition, which deciphers context-driven intercellular communication by simultaneously accounting for multiple stages, states, or locations of the cells. To do so, Tensor-cell2cell uncovers context-driven patterns of communication associated with different phenotypic states and determined by unique combinations of cell types and ligand-receptor pairs. As such, Tensor-cell2cell robustly improves upon and extends the analytical capabilities of existing tools. We show Tensor-cell2cell can identify multiple modules associated with distinct communication processes (e.g., participating cell-cell and ligand-receptor pairs) linked to severities of Coronavirus Disease 2019 and to Autism Spectrum Disorder. Thus, we introduce an effective and easy-to-use strategy for understanding complex communication patterns across diverse conditions.

Birdsong as a window into language origins and evolutionary neuroscience.

Humans and songbirds share the key trait of vocal learning, manifested in speech and song, respectively. Striking analogies between these behaviours include that both are acquired during developmental critical periods when the brain's ability for vocal learning peaks. Both behaviours show similarities in the overall architecture of their underlying brain areas, characterized by cortico-striato-thalamic loops and direct projections from cortical neurons onto brainstem motor neurons that control the vocal organs. These neural analogies extend to the molecular level, with certain song control regions sharing convergent transcriptional profiles with speech-related regions in the human brain. This evolutionary convergence offers an unprecedented opportunity to decipher the shared neurogenetic underpinnings of vocal learning. A key strength of the songbird model is that it allows for the delineation of activity-dependent transcriptional changes in the brain that are driven by learned vocal behaviour. To capitalize on this advantage, we used previously published datasets from our laboratory that correlate gene co-expression networks to features of learned vocalization within and after critical period closure to probe the functional relevance of genes implicated in language. We interrogate specific genes and cellular processes through converging lines of evidence: human-specific evolutionary changes, intelligence-related phenotypes and relevance to vocal learning gene co-expression in songbirds. This article is part of the theme issue 'What can animal communication teach us about human language?'

FoxP2 isoforms delineate spatiotemporal transcriptional networks for vocal learning in the zebra finch.

Human speech is one of the few examples of vocal learning among mammals yet ~half of avian species exhibit this ability. Its neurogenetic basis is largely unknown beyond a shared requirement for FoxP2 in both humans and zebra finches. We manipulated FoxP2 isoforms in Area X, a song-specific region of the avian striatopallidum analogous to human anterior striatum, during a critical period for song development. We delineate, for the first time, unique contributions of each isoform to vocal learning. Weighted gene coexpression network analysis of RNA-seq data revealed gene modules correlated to singing, learning, or vocal variability. Coexpression related to singing was found in juvenile and adult Area X whereas coexpression correlated to learning was unique to juveniles. The confluence of learning and singing coexpression in juvenile Area X may underscore molecular processes that drive vocal learning in young zebra finches and, by analogy, humans.