Large-scale associations between the leukocyte transcriptome and BOLD responses to speech differ in autism early language outcome subtypes

Lombardo, Michael; Pramparo, Tiziano; Gazestani, Vahid H.; Warrier, Varun; Bethlehem, Richard A. I.; Barnes, Cynthia Carter; Lopez, Linda; Lewis, Nathan E.; Eyler, Lisa T.; Pierce, Karen; Courchesne, Eric

doi:10.1038/s41593-018-0281-3

Cited by 79 publications

(117 citation statements)

References 78 publications

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“…Rather, our observations only require cross-tissue stability in the proximal impact of a CNV on expression of CNV region genes, and this phenomenon already has good empirical support from studies in different tissues of aneuploidic plants 33 , as well as from our own comparison of altered expression of chromosome 21 genes in brain and LCL tissues from patients with Down syndrome (see above). Future work examining the coordinated impact of other CNVs on brain anatomy and gene expression, as well as in other idiopathic neurodevelopmental disorders 35 , will be critical in substantiating the generalizability of these findings. In general, however, prediction of neuroanatomical phenotypes in CNV carriers from easily gathered measures of peripheral gene expression represents an important proof-ofprinciple that could open up new avenues towards advances in personalized medicine for CNV-based brain disorders.…”

Section: Discussionmentioning

confidence: 94%

Transcriptomic and Cellular Decoding of Regional Brain Vulnerability to Neurodevelopmental Disorders

Seidlitz¹,

Nadig²,

Liu³

et al. 2019

Preprint

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Neurodevelopmental disorders are highly heritable and associated with spatially-selective disruptions of brain anatomy. The logic that translates genetic risks into spatially patterned brain vulnerabilities remains unclear but is a fundamental question in disease pathogenesis. Here, we approach this question by integrating (i) in vivo neuroimaging data from patient subgroups with known causal genomic copy number variations (CNVs), and (ii) bulk and single-cell gene expression data from healthy cortex. First, for each of six different CNV disorders, we show that spatial patterns of cortical anatomy change in youth are correlated with spatial patterns of expression for CNV region genes in bulk cortical tissue from typically-developing adults. Next, by transforming normative bulk-tissue cortical expression data into cell-type expression maps, we further link each disorder's anatomical change map to specific cell classes and specific CNV-region genes that these cells express. Finally, we establish convergent validity of this "transcriptional vulnerability model" by inter-relating patient neuroimaging data with measures of altered gene expression in both brain and bloodderived patient tissue. Our work clarifies general biological principles that govern the mapping of genetic risks onto regional brain disruption in neurodevelopmental disorders. We present new methods that can harness these principles to screen for potential cellular and molecular determinants of disease from readily available patient neuroimaging data.

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Section: Discussionmentioning

confidence: 94%

Transcriptomic and Cellular Decoding of Regional Brain Vulnerability to Neurodevelopmental Disorders

Seidlitz¹,

Nadig²,

Liu³

et al. 2019

Preprint

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“…Similar to recent work from our group that assessed functional hierarchy in autism 6 , structural manifold features used in this study were particularly useful in predicting impairments in lower-level repetitive behavior symptoms as well as higher-order social and cognitive deficits, but not very sensitive in predicting atypical communication abilities. The inability of our approach to predict communication deficits remains to be investigated further, but it may potentially relate to other aspects of autism spectrum heterogeneity, including speech onset delay that affects only a subgroup of autism individuals and potentially associated compensatory mechanisms between sensory and language networks [106][107][108] .…”

Section: Discussionmentioning

confidence: 99%

Connectome and microcircuit models implicate atypical subcortico-cortical interactions in autism pathophysiology

Park

Hong

Valk

et al. 2020

Preprint

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Both macroscale connectome miswiring and microcircuit anomalies have been suggested to play a role in the pathophysiology of autism. However, an overarching framework that consolidates these macro and microscale perspectives of the condition is lacking. Here, we combined connectome-wide manifold learning and biophysical simulation models to understand associations between global network perturbations and microcircuit dysfunctions in autism. Our analysis established that autism showed significant differences in structural connectome organization relative to neurotypical controls, with strong effects in low-level somatosensory regions and moderate effects in high-level association cortices. Computational models revealed that the degree of macroscale anomalies was related to atypical increases of subcortical inputs into cortical microcircuits, especially in sensory and motor areas. Transcriptomic decoding and developmental gene enrichment analyses provided biological context and pointed to genes expressed in cortical and thalamic areas during childhood and adolescence. Supervised machine learning showed the macroscale perturbations predicted sociocognitive symptoms and repetitive behaviors. Our analyses provide convergent support that atypical subcortico-cortical interactions may contribute to both microcircuit and macroscale connectome anomalies in autism.

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“…For example, rASD genes are linked to biological processes related to non-neuronal cell types including microglia, astrocytes, and leukocytes (Ballas et al, 2009;Derecki et al, 2012;Gupta et al, 2014;Kasah et al, 2018;Pramparo et al, 2015;Suzuki et al, 2013;Voineagu et al, 2011). Likewise, genetic variants related to brain processes, diseases, and disorders can modulate gene expression in cell types other than neurons and tissues other than brain (Lin et al, 2018;Lombardo et al, 2018;Pardinas et al, 2018;Wright et al, 2014). ASD risk genes include both broadly-expressed and brain-specific genes with temporally different expression patterns.…”

Section: Introductionmentioning

confidence: 99%

Autism genetics perturb prenatal neurodevelopment through a hierarchy of broadly-expressed and brain-specific genes

Gazestani¹,

Chiang²,

Courchesne³

et al. 2020

Preprint

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Numerous genes are associated with autism spectrum disorder (ASD); however, it remains unclear how most ASD risk genes influence neurodevelopment and result in similar traits. Recent genetic models of complex traits suggest non-tissue-specific genes converge on core disease genes; so we analyzed ASD genetics in this context. We found ASD risk genes partition cleanly into broadly-expressed and brain-specific genes. The two groups show sequential roles during neurodevelopment with broadly-expressed genes modulating chromatin remodeling, proliferation, and cell fate, while brain-specific risk genes are involved in neural maturation and synapse functioning. Broadly-expressed risk genes converge onto brain-specific risk genes and core neurodevelopmental genes through regulatory networks including PI3K/AKT, RAS/ERK, and WNT/ -catenin signaling pathways. Broadly-expressed and brain-specific risk genes show unique properties, wherein the broadly-expressed risk gene network is expressed prenatally and conserved in non-neuronal cells like microglia. However, the brain-specific gene network expression is limited to excitatory and inhibitory neurons, spanning prenatal to adulthood. Furthermore, the two groups are linked differently to comorbidities associated with ASD. Collectively, we describe here the organization of the genetic architecture of ASD as a hierarchy of broadlyexpressed and brain-specific genes that disrupt successive stages of core neurodevelopmental processes.Recent studies present an alternate model of complex traits where the functional impact of genetic aberrations propagates through gene regulatory networks to converge on downstream core processes related to the trait (Boyle et al., 2017;Califano and Alvarez, 2017;Courchesne et al., 2020;Gazestani et al., 2019;Iakoucheva et al., 2019;Liu et al., 2019). In contrast to the single-group rASD network model, if the polygenic and omnigenic models are relevant to ASD, they would suggest that many risk genes are not necessarily part of underlying neural mechanisms in ASD. Rather many rASD genes would be broadly-expressed across many tissues, but regulate core neurodevelopmental processes underlying ASD (Boyle et al., 2017;Califano and Alvarez, 2017;Courchesne et al., 2020;Gazestani et al., 2019). Moreover, by emphasizing the gene regulatory networks, these alternative models suggest that, to the extent that the gene regulatory networks are preserved, the dysregulation could also be reflected in non-neuronal cells . Supporting these ideas, many rASD genes are broadly-expressed across tissues and strongly enriched for gene expression regulators such as chromatin remodelers, transcription factors, and modulators of signaling pathways (Courchesne et al., 2020;Courchesne et al., 2019;Werling et al., 2020). Similarly, genome wide association studies (GWAS) and whole genome sequencing both highlight the important role of broadly functional eQTLs and gene regulatory networks in ASD liability (Brandler et al., 2018;Courchesne et al., 2020;Grove et al., 2019).The fundamen...

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Large-scale associations between the leukocyte transcriptome and BOLD responses to speech differ in autism early language outcome subtypes

Cited by 79 publications

References 78 publications

Transcriptomic and Cellular Decoding of Regional Brain Vulnerability to Neurodevelopmental Disorders

Transcriptomic and Cellular Decoding of Regional Brain Vulnerability to Neurodevelopmental Disorders

Connectome and microcircuit models implicate atypical subcortico-cortical interactions in autism pathophysiology

Autism genetics perturb prenatal neurodevelopment through a hierarchy of broadly-expressed and brain-specific genes

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