This is a preprint.

It has not yet been peer reviewed by a journal.

The National Library of Medicine is running a pilot to include preprints that result from research funded by NIH in PMC and PubMed.

[Preprint]. 2025 Feb 8:2025.02.07.637106.

doi: 10.1101/2025.02.07.637106.

Early cell cycle genes in cortical organoid progenitors predict interindividual variability in infant brain growth trajectories

Madison R Glass^{1

2

3}, Nana Matoba^{1

2

3}, Alvaro A Beltran^{1

2}, Niyanta K Patel^{1

2}, Tala M Farah^{1

2}, Karthik Eswar^{1

2}, Shivam Bhargava^{1

2}, Karen Huang^{1

2}, Ian Curtin^{1

2}, Sara Ahmed^{1

2}, Mary Srivastava^{1

2}, Emma Drake^{1

2}, Liam T Davis^{1

2}, Meghana Yeturi^{1

2}, Kexin Sun^{1

2}, Michael I Love^{1

4}, Jeremy M Simon^{1

2

5

6}, Tanya St John^{7

8}, Natasha Marrus⁹, Juhi Pandey^{10

11

12}, Annette Estes^{7

8}, Stephen Dager^{13

14}, Robert T Schultz^{10

11

12}, Kelly Botteron⁹, Alan Evans^{15

16

17}, Sun Hyung Kim¹⁸, Martin Styner^{18

19

20}, Robert C McKinstry⁹, D Louis Collins^{15

17}, Heather Volk²¹, Kelly Benke²¹, Lonnie Zwaigenbaum²², Heather Hazlett^{18

19}, Adriana S Beltran¹, Jessica B Girault^{18

19

23}, Mark D Shen^{2

18

19

23}, Joseph Piven^{18

19

23}, Jason L Stein^{1

2

18

23

24}; Infant Brain Imaging Study Network

Affiliations

¹ Department of Genetics, University of North Carolina at Chapel Hill; Chapel Hill, NC, USA.
² UNC Neuroscience Center, University of North Carolina at Chapel Hill; Chapel Hill, NC, USA.
³ These authors contributed equally.
⁴ Department of Biostatistics, University of North Carolina at Chapel Hill; Chapel Hill, NC, USA.
⁵ Present address: Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA.
⁶ Present address: Department of Biostatistics, Harvard T.H. Chan School of Public Health, MA, USA.
⁷ Department of Speech and Hearing Sciences, University of Washington; Seattle, WA, USA.
⁸ University of Washington Autism Center, University of Washington; Seattle, WA, USA.
⁹ Department of Psychiatry, Washington University School of Medicine; St. Louis, MO, USA.
¹⁰ Department of Psychiatry, University of Pennsylvania; Philadelphia, PA, USA.
¹¹ Center for Autism Research, Children's Hospital of Philadelphia; Philadelphia, PA, USA.
¹² Department of Pediatrics, University of Pennsylvania; Philadelphia, USA.
¹³ Department of Radiology, University of Washington; Seattle, WA, USA.
¹⁴ Department of Bioengineering, University of Washington; Seattle, WA, USA.
¹⁵ Department of Neurology and Neurosurgery, McGill University; Montreal, QC, CA.
¹⁶ Department of Psychiatry, McGill University; Montreal, QC, CA.
¹⁷ Department of Biomedical Engineering, McGill University; Montreal, QC, CA.
¹⁸ Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill; Chapel Hill, NC, USA.
¹⁹ Department of Psychiatry, University of North Carolina at Chapel Hill; Chapel Hill, NC, USA.
²⁰ Department of Computer Sciences, University of North Carolina at Chapel Hill; Chapel Hill, NC, USA.
²¹ School of Public Health, Johns Hopkins; Baltimore, MD, USA.
²² Department of Developmental Pediatrics, University of Alberta; Edmonton, AB, CA.
²³ These authors jointly supervised.
²⁴ Lead contact.

PMID: 39974968
PMCID: PMC11839139
DOI: 10.1101/2025.02.07.637106

Early cell cycle genes in cortical organoid progenitors predict interindividual variability in infant brain growth trajectories

Madison R Glass et al. bioRxiv. 2025.

[Preprint]. 2025 Feb 8:2025.02.07.637106.

doi: 10.1101/2025.02.07.637106.

Authors

Affiliations

¹ Department of Genetics, University of North Carolina at Chapel Hill; Chapel Hill, NC, USA.
² UNC Neuroscience Center, University of North Carolina at Chapel Hill; Chapel Hill, NC, USA.
³ These authors contributed equally.
⁴ Department of Biostatistics, University of North Carolina at Chapel Hill; Chapel Hill, NC, USA.
⁵ Present address: Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA.
⁶ Present address: Department of Biostatistics, Harvard T.H. Chan School of Public Health, MA, USA.
⁷ Department of Speech and Hearing Sciences, University of Washington; Seattle, WA, USA.
⁸ University of Washington Autism Center, University of Washington; Seattle, WA, USA.
⁹ Department of Psychiatry, Washington University School of Medicine; St. Louis, MO, USA.
¹⁰ Department of Psychiatry, University of Pennsylvania; Philadelphia, PA, USA.
¹¹ Center for Autism Research, Children's Hospital of Philadelphia; Philadelphia, PA, USA.
¹² Department of Pediatrics, University of Pennsylvania; Philadelphia, USA.
¹³ Department of Radiology, University of Washington; Seattle, WA, USA.
¹⁴ Department of Bioengineering, University of Washington; Seattle, WA, USA.
¹⁵ Department of Neurology and Neurosurgery, McGill University; Montreal, QC, CA.
¹⁶ Department of Psychiatry, McGill University; Montreal, QC, CA.
¹⁷ Department of Biomedical Engineering, McGill University; Montreal, QC, CA.
¹⁸ Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill; Chapel Hill, NC, USA.
¹⁹ Department of Psychiatry, University of North Carolina at Chapel Hill; Chapel Hill, NC, USA.
²⁰ Department of Computer Sciences, University of North Carolina at Chapel Hill; Chapel Hill, NC, USA.
²¹ School of Public Health, Johns Hopkins; Baltimore, MD, USA.
²² Department of Developmental Pediatrics, University of Alberta; Edmonton, AB, CA.
²³ These authors jointly supervised.
²⁴ Lead contact.

PMID: 39974968
PMCID: PMC11839139
DOI: 10.1101/2025.02.07.637106

Abstract

Human induced pluripotent stem cell (iPSC) derived cortical organoids (hCOs) model neurogenesis on an individual's genetic background. The degree to which hCO phenotypes recapitulate the brain growth of the participants from which they were derived is not well established. We generated up to 3 iPSC clones from each of 18 participants in the Infant Brain Imaging Study, who have undergone longitudinal brain imaging during infancy. We identified consistent hCO morphology and cortical cell types across clones from the same participant. hCO cross-sectional area and production of cortical hem cells were associated with in vivo cortical growth rates. Cell cycle associated genes expression in early progenitors at the crux of fate decision trajectories were correlated with cortical growth rate from 6-12 months of age, and were enriched in microcephaly and neurodevelopmental disorder genes. Our data suggest the hCOs capture inter-individual variation in cortical cell types influencing infant cortical surface area expansion.

Keywords: Cell cycle; WNT; cortical hem; infant brain growth; neurogenesis; organoid.

PubMed Disclaimer

Conflict of interest statement

Declaration of Interests Robert McKinstry received travel and meals from Siemens Healthcare and Radiaction, meals from Myperfine, holds stock options in Turing Medical and serves on its advisory board. The authors declare no other competing interests.

Figures

**Fig. 1.. Strategy to Model Inter-Individual Variation in Infant MRI Measures using Cortical Organoids**
a, Experimental Overview. Previous Infant Brain Imaging Study (IBIS) research collected longitudinal MRI measurements from three groups of participants: Infants with no family history (low-likelihood, LL) of neuropsychiatric disorders, infants with an older sibling diagnosed with autism spectrum disorder (ASD) who either were not diagnosed at 24 months of age (high likelihood, HL) or received an ASD diagnosis (high likelihood - ASD, HL-ASD). Up to 3 iPSC clones were generated from previous IBIS participants’ PBMCs. iPSC lines were differentiated into cortical organoids and assayed with scRNAseq at day 14 and day 84, 3D imaged at day 14, and imaged throughout the differentiation to measure cross-sectional area and organoid morphology. b, MRI measurements of cortical surface area in IBIS participants in the study. c, correlations among MRI measurements of IBIS participants in this study. # indicates FDR < 0.1 d, scRNAseq cell type annotations. e, Representative day 14 organoid showing NCAD+ neuroepithelial buds with PAX6+ radial glia. f, Day 84 organoids showing CTIP2+ lower layer neurons outside of neuroepithelial buds. Abbreviation: oligodendrocytes (OL), oligodendrocyte progenitor cells (OPC), intermediate progenitor cell (IPC), excitatory neuron (EN), inhibitory neuron (IN), radial glia (RG), apical radial glia (aRG), outer radial glia (oRG), truncated radial glia (tRG), ventral radial glia (vRG), cortical projection neuron (CPN), deep layer projection neuron (DLPN), Cycling progenitor (Cyc. prog.), pre-plate (PP), subplate (SP).

**Fig. 2. Consistency of differentiation across participants in morphology and cell class proportions.**
a, Day 14 morphology rank indicates if visible neuroepithelial buds were present or if there was growth into the matrigel. b, Day 56 morphology rank indicates if clear cysts were present on the organoid. c, Quantification of percent rank across day 14 and day 56 for each clone. d, Correlation across and within participants for all percent morphological ranks. e, Cell class proportion for each library. Libraries from the same differentiation day and clone prepared in different scRNA-seq library preparations are indicated by a bracket. f, PCA plot of cell class proportions for samples passing QC. g, Cell type proportions contributing to principal components. The top 5 contributing subclusters are labeled. h, Correlation of major cell classes across and within participants at day 14 (top) and day 84 (bottom).

**Fig. 3.. Cell Type Proportion Correlate to MRI.**
a. Average day 14 cell type proportions associated with cortical surface area measurements. b. Average day 84 cell type proportions associated with cortical surface area measurements. FDR was calculated for either subclusters or cell classes at each timepoint across MRI measurements. Correlation between cortical surface area growth between 6-12 months of age and day 14 for c. cortical hem d. sc_10 (cortical hem) and e. sc_8 (cortical hem) proportions. Sex is added as a covariate and age at MRI is a covariate for cross-sectional MRI measurements. Day 84 IP association with 12-24 month growth rate was driven by one clone of one donor, so is not highlighted as a scatterplot.

**Fig. 4. hCO Cross Sectional associations with cortical growth.**
a. hCO cross-sectional area growth rate for each differentiation over time and example mask of an area measurement across differentiation days (inset). b. Correlation of cross-sectional area measurements at all timepoints across and within participants. c. Cross-sectional area correlations to cortical structure measurements using the average measurements across all differentiated clones. FDR correction was applied for each area measurement to all MRI measurements. Correlations between day 7 and day 14 hCO growth rate with d. 6-12 month cortical surface area growth rate, e. 12-24 month cortical surface area growth rate and f. 24 month cortical surface area.

**Fig. 5.. Gene expression levels are associated with surface area and growth rate**
a, Heatmap showing the distribution of gene counts associated with brain growth rate (left) and surface area (right) across subclusters and time points. Color intensity indicates the number of associated genes. In the subsequent panels, we focus on genes associated with sc_22 at day 14 for growth rate (6-12) and surface area at 12 months. b, UpsetR plot summarizing gene overlaps, c, Pathway enrichment analysis of associated genes, with key pathways such as “*RHO GTPase effectors”*, “*Cell Cycle”*. d, Scatter plots demonstrating correlations between sex-corrected growth rate and gene expression (three examples from RHO GTPase effectors). e, PCA of gene expression from subset major cell types (Upper layer neuron (ULN), Inhibitory neuron (IN), cortical projection neuron (CPN), newborn deep layer projection neuron (DPLN), outer radial glia (oRG), apical radial glia (aRG)) colored by cell class (left). Extracted cells from sc_22 on the same dimension in the left panel. Color intensity indicates cell count density (right). Three lineages (ULN: purple, newborn neuron: blue, RG: red) were annotated using inferred pseudotime. f, Genes positively associated with brain growth or surface area were enriched in microcephaly and ASD.

See this image and copyright information in PMC

References

1. Gordon A. et al. Long-term maturation of human cortical organoids matches key early postnatal transitions. Nat. Neurosci. 24, 331–342 (2021). - PMC - PubMed
1. Kelley K. W. & Pașca S. P. Human brain organogenesis: Toward a cellular understanding of development and disease. Cell 185, 42–61 (2022). - PubMed
1. Di Lullo E. & Kriegstein A. R. The use of brain organoids to investigate neural development and disease. Nat. Rev. Neurosci. 18, 573–584 (2017). - PMC - PubMed
1. Glass M. R. et al. Cross-site reproducibility of human cortical organoids reveals consistent cell type composition and architecture. Stem Cell Reports 0, (2024). - PMC - PubMed
1. Yoon S.-J. et al. Reliability of human cortical organoid generation. Nat. Methods 16, 75–78 (2019). - PMC - PubMed

Save citation to file

Email citation

Add to Collections

Add to My Bibliography

Your saved search

Create a file for external citation management software

Your RSS Feed

This is a preprint.

Early cell cycle genes in cortical organoid progenitors predict interindividual variability in infant brain growth trajectories

Affiliations

Early cell cycle genes in cortical organoid progenitors predict interindividual variability in infant brain growth trajectories

Authors

Affiliations

Abstract

Conflict of interest statement

Figures

References

Publication types

Grants and funding

LinkOut - more resources

Full Text Sources