⚡️Our findings have implications for understanding how prenatal stressors can shape brain function and contribute to mental health disorders later in life. A critical step toward bridging the gap between genetics and environment in brain health.

Check out the press release ⬇️ […]

⚠️ Why it matters: We show how environmental factors, like GC exposure, can converge to affect brain development through common molecular mechanisms as genetic risk factors: priming of the inhibitory neuron lineage.

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We identified PBX3 as an example of a TF that is closely linked to the inhibitory neuron lineage priming. In silico perturbation experiments of multimodal GRNs suggest PBX3 as a potential mediator of the effect. 🧬🔑

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Our findings show that chronic GC exposure alters lineage specification, with a selective priming of the inhibitory neuron lineage. 🧠

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In our study, we looked at how chronic GC exposure affects neural differentiation and lineage specification in human neural organoids, using single-cell techniques to map the molecular changes in detail. 🔬🧬

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Thanks to our amazing PIs @graycamplab.bsky.social , @fabiantheis.bsky.social, and Barbara Treutlein for all their guidance and support! 🚀
This work is part of the larger Human Cell Atlas effort to map all human cells. Explore more @natureportfolio.bsky […]

[Original post on mastodon.social]

A huge thank you to all collaborators: @chatgtp.bsky.social, @katelynxli.bsky.social, Irena Slišković, Hsiu-Chuan Lin, Malgorzata Santel, Alexander Atamian, @giorgiaquadrato.bsky.social, Jieran Sun, @sergiuppasca.bsky.social & the Human Cell Atlas Organoid Biological Network. 🙏

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Contextualising New Data 🗺: The atlas serves as a powerful tool for annotating cell types, comparing protocols, and contextualising your new neural organoid scRNA-seq dataset. We provide a Python package (https://github.com/devsystemslab/HNOCA-tools/) and interactive web interface (through […]

Disease Modeling 😷 : Our atlas can be leveraged as a diverse control cohort to contextualise organoid models of disease, helping identify underlying genes and pathways. We found that comprehensive control data is vital for disentangling disease from regional effects.

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Quantifying Organoid Fidelity 📊: By estimating the transcriptomic similarity between primary and organoid brain counterparts, we provide a robust framework for assessing protocol variation and fidelity across labs and methods. Cell stress seems to be quite dependent on protocol.

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Identifying Missing Cell States 🔍: We map neural organoid cell types and states to a developing human brain reference, highlighting gaps in the diversity of brain regions present in current in vitro models. ⚠️While the telencephalon seems well-captured […]

[Original post on mastodon.social]

Introducing the Human Neural Organoid Cell Atlas 🗺️: We’ve integrated 36 neural organoid datasets across 26 protocols. This produced a comprehensive, integrated reference atlas, including a hierarchical cell-type annotation, partially derived by mapping to primary human 🧠.

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