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Impaired neurogenesis alters brain biomechanics in a neuroprogenitor-based genetic subtype of congenital hydrocephalus

Nature Neuroscience volume 25, pages 458–473 (2022)Cite this article

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Abstract

Hydrocephalus, characterized by cerebral ventricular dilatation, is routinely attributed to primary defects in cerebrospinal fluid (CSF) homeostasis. This fosters CSF shunting as the leading reason for brain surgery in children despite considerable disease heterogeneity. In this study, by integrating human brain transcriptomics with whole-exome sequencing of 483 patients with congenital hydrocephalus (CH), we found convergence of CH risk genes in embryonic neuroepithelial stem cells. Of all CH risk genes, TRIM71/lin-41 harbors the most de novo mutations and is most specifically expressed in neuroepithelial cells. Mice harboring neuroepithelial cell-specific Trim71 deletion or CH-specific Trim71 mutation exhibit prenatal hydrocephalus. CH mutations disrupt TRIM71 binding to its RNA targets, causing premature neuroepithelial cell differentiation and reduced neurogenesis. Cortical hypoplasia leads to a hypercompliant cortex and secondary ventricular enlargement without primary defects in CSF circulation. These data highlight the importance of precisely regulated neuroepithelial cell fate for normal brain–CSF biomechanics and support a clinically relevant neuroprogenitor-based paradigm of CH.

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Fig. 1: Convergence of CH genetic risk in discrete gene networks and cell types during human brain development.
Fig. 2: A mouse model that harbors the murine homolog (R595H) of the human CH-associated missense mutation in TRIM71 (R608H) exhibits ventriculomegaly and cortical hypoplasia.
Fig. 3: TRIM71 is expressed in neuroepithelial cells and is required in embryonic neuroprogenitors for forebrain morphogenesis.
Fig. 4: Mutant TRIM71 alters neural stem cell progression, leading to premature differentiation with reduced proliferation.
Fig. 5: Development of secondary aqueductal stenosis due to forebrain ventriculomegaly in hydrocephalic Trim71R595H/+ mice.
Fig. 6: Abnormal brain biomechanics facilitates secondary ventricular dilation in hydrocephalic Trim71R595H/+ mice.
Fig. 7: CH mutations impair TRIM71 binding to its RNA targets, including the novel target Spred1.
Fig. 8: Graphical summary of findings.

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Resource availability

All unique animal lines and cell lines in this study are available upon reasonable request to the corresponding author. Source data are provided with this paper.

Data availability

Unprocessed scans of all immunoblots in the paper are included as Source Data Fig. 1. WES data have been deposited in the database of Genotypes and Phenotypes under accession number phs000744. A Life Sciences Reporting Summary is available for this paper. In-house pipelines are available from the corresponding author upon reasonable request. Bulk RNA sequencing data of mESCs have been deposited at the Gene Expression Omnibus under accession number GSE189420. Source data are provided with this paper.

Code availability

All code used in this paper is available from the corresponding author upon reasonable request.

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Acknowledgements

This work was supported by T32GM136651 (to P.Q.D.), F30HD106694 (to P.Q.D.), RO1NS111029 (to K.T.K.), David M. Rubenstein Fund for Hearing Research (to A. Doetzlhofer), 1R21NS121642-01 (to X.Y.), 1R01NS122904-01 (to X.Y.), the Rudi Schulte Institute (to K.T.K.), the Hydrocephalus Association Innovator Award (to K.T.K., E.D. and S.J.C.), 5R21NS116484-02 (to E.D.), National Institutes of Health (NIH)/National Heart, Lung, and Blood Institute (NHLBI) Pathway to Independence award R00HL143036-02 (to S.J.C.), Clinical & Translational Research Funding Program award CTSA1405 (to S.J.C.), Children’s Discovery Institute Faculty Scholar award CDI-FR-2021-926 (to S.J.C.), NIH Director’s New Innovator award 1DP2AI138259-01 (to N.S.M.), the Career Award at the Scientific Interfaces from Burroughs Welcome Fund (to N.S.M.), the Hartwell Foundation Individual Biomedical Research Award (to N.S.M.), MacBrainResource NIH MH113257 (to A. Duque), NIH DA023999 (to P.R.) and Deutsche Forschungsgemeinschaft (German Research Foundation) award WU 563/3-1 (to F.G.W.). W.K. is funded by the Deutsche Forschungsgemeinschaft under Germany’s Excellence Strategy EXC2151–390873048. All mechanical measurements were performed at the Yale West Campus Imaging Core. CSF outflow imaging was performed using the small animal imaging facility of the Center for Precision Cancer Modeling, sponsored by the Yale Cancer Center. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. Certain cartoons and diagrams were generated using BioRender.

Author information

Author notes

  1. These authors contributed equally: Phan Q. Duy, Stefan C. Weise.

Authors and Affiliations

  1. Department of Neuroscience and Kavli Institute for Neuroscience, Yale University School of Medicine, New Haven, CT, USA

    Phan Q. Duy, Dan Liang, Shaojie Ma, Ana Spajic, André M. M. Sousa, Fuchen Liu, Suel-Kee Kim, Mingfeng Li, Alvaro Duque, Pasko Rakic & Nenad Sestan

  2. Department of Neurosurgery, Yale University School of Medicine, New Haven, CT, USA

    Phan Q. Duy, Emre Kiziltug, Adam J. Kundishora, Le Thi Hao, Yutaka Takeo, Stephanie M. Robert, Amrita K. Singh, Garrett Allington, Charuta G. Furey, Benjamin C. Reeves, Hannah Smith, Ashley Dunbar, Tyrone DeSpenza Jr. & Arnaud Marlier

  3. Medical Scientist Training Program, Yale University School of Medicine, New Haven, CT, USA

    Phan Q. Duy

  4. Molecular Immunology and Cell Biology, Life & Medical Sciences Institute (LIMES), University of Bonn, Bonn, Germany

    Stefan C. Weise, Lucia A. Torres-Fernández, Bettina Jux & Waldemar Kolanus

  5. Institute for Cell Biology and Neurobiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany

    Claudia Marini & F. Gregory Wulczyn

  6. Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA

    Xiao-Jun Li & Angelika Doetzlhofer

  7. Center for Hearing and Balance, Department of Otolaryngology-Head and Neck Surgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA

    Xiao-Jun Li & Angelika Doetzlhofer

  8. Microbial Sciences Institute, Yale University, West Haven, CT, USA

    Peter J. Dahl & Nikhil S. Malvankar

  9. Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA

    Peter J. Dahl & Nikhil S. Malvankar

  10. Laboratory of Human Genetics and Genomics, The Rockefeller University, New York, NY, USA

    Weilai Dong & Richard P. Lifton

  11. GeneDx, Gaithersburg, MD, USA

    Jane Juusola

  12. Department of Anesthesiology, Yale University School of Medicine, New Haven, CT, USA

    Sunil Koundal, Maysam Z. Pedram & Helene Benveniste

  13. Systems Medicine, Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), Bonn, Germany

    Kristian Händler, Elena De Domenico, Matthias Becker, Thomas Ulas & Joachim L. Schultze

  14. Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany

    Kristian Händler, Elena De Domenico, Matthias Becker, Thomas Ulas & Joachim L. Schultze

  15. Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE). PRECISE Platform for Genomics and Epigenomics at DZNE and University of Bonn, Bonn, Germany

    Kristian Händler, Elena De Domenico, Matthias Becker, Thomas Ulas & Joachim L. Schultze

  16. Department of Oncology, Hematology and Rheumatology, University Hospital Bonn, Bonn, Germany

    Stefan A. Juranek & Katrin Paeschke

  17. Stem Cells and Regenerative Medicine Section, University College London Great Ormond Street Institute of Child Health, London, UK

    Elisa Cuevas

  18. Yale Stem Cell Center, Yale University School of Medicine, New Haven, CT, USA

    Yiying Yang & Haifan Lin

  19. Department of Genetics, Yale University School of Medicine, New Haven, CT, USA

    Carol Nelson-Williams & Andrew T. Timberlake

  20. Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA

    Yonghyun Ha, Kartiga Selvaganesan, Evelyn M. R. Lake & R. Todd Constable

  21. Division of Pediatric Neurosurgery, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA

    June Goto

  22. Department of Radiology, Autism & Developmental Medicine Institute, Genomic Medicine Institute, Geisinger, Danville, PA, USA

    Andres Moreno-De-Luca

  23. Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA

    Xin Yu, William E. Butler, Bob S. Carter & Kristopher T. Kahle

  24. Department of Pediatrics, Yale University School of Medicine, New Haven, CT, USA

    Engin Deniz

  25. Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, USA

    Juvianee I. Estrada-Veras

  26. Pediatric Subspecialty Genetics Walter Reed National Military Medical Center, Bethesda, MD, USA

    Juvianee I. Estrada-Veras

  27. Murtha Cancer Center/Research Program, Department of Surgery, Uniformed Services University of the Health Sciences, Bethesda, MD, USA

    Juvianee I. Estrada-Veras

  28. Division of Genetics and Genomics, Manton Center for Orphan Disease Research, Department of Pediatrics, and Howard Hughes Medical Institute, Boston Children’s Hospital, Boston, MA, USA

    Christopher A. Walsh & Kristopher T. Kahle

  29. Departments of Pediatrics and Neurology, Harvard Medical School, Boston, MA, USA

    Christopher A. Walsh

  30. Broad Institute of MIT and Harvard, Cambridge, MA, USA

    Christopher A. Walsh, Seth L. Alper & Kristopher T. Kahle

  31. Division of Nephrology and Vascular Biology Research Center, Beth Israel Deaconess Medical Center and Department of Medicine, Harvard Medical School, Boston, MA, USA

    Seth L. Alper

  32. Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA

    Sheng Chih Jin

  33. Harvard Center for Hydrocephalus and Neurodevelopmental Disorders, Massachusetts General Hospital, Boston, MA, USA

    Kristopher T. Kahle

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  1. Phan Q. Duy
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Contributions

Conceptualization of the project: P.Q.D., S.C.W., W.K. and K.T.K. Data collection: P.Q.D., S.C.W., C.M., X.L., D.L., P.J.D., S.M., A.S., W.D., J.J., E.K., A.J.K., S.K., M.Z.P., L.A.T.-F., K.H., E.D.D., M.B., T.U., S.A.J., E.C., L.T.H., B.J., A.M.M.S., F.L., S.-K.K., M.L., Y.Y., Y.T., A. Duque, C.N.-W., Y.H., K.S., S.M.R., A.K.S., G.A., C.G.F., A.T.T., B.C.R., H.S., A. Dunbar, T.D., J.G., A.M., A.M.-D.-L., X.Y., W.E.B., B.S.C., E.M.R.L., R.T.C., P.R., H.L., E.D., H.B., N.M., J.I.E.-V., C.A.W., S.L.A., J.S., K.P., A. Doetzlhofer, F.G.W., S.C.J., R.P.L., N.S., W.K. and K.T.K. Data analysis: P.Q.D., S.C.W., C.M., X.L., D.L., P.J.D., S.M., A.S., W.D., J.J., E.K., A.J.K., S.K., M.Z.P., L.A.T.-F., K.H., E.D.D., M.B., T.U., S.A.J., E.C., L.T.H., B.J., A.M.M.S., F.L., S.-K.K., M.L., Y.Y., Y.T., A. Duque, C.N.-W., Y.H., K.S., S.M.R., A.K.S., G.A., C.G.F., A.T.T., B.C.R., H.S., A. Dunbar, T.D., J.G., A.M., A.M.-D.-L., X.Y., W.E.B., B.S.C., E.M.R.L., R.T.C., P.R., H.L., E.D., H.B., N.M., J.I.E.-V., C.A.W., S.L.A., J.S., K.P., A. Doetzlhofer, F.G.W., S.C.J., R.P.L., N.S., W.K. and K.T.K. Writing: P.Q.D., S.C.W., W.K. and K.T.K., with input from all authors.

Corresponding author

Correspondence to Kristopher T. Kahle.

Ethics declarations

Competing interests

J.J. is an employee of GeneDx, Inc.

Peer review

Peer review information

Nature Neuroscience thanks the anonymous reviewers for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Integrative genomic analysis of CH genetic risk.

a) Heatmap showing expression of CH risk genes across developmental timepoints and regions of the developing human brain. Analyzed transcriptomic dataset from12. b) Enrichment of CH risk genes across developmental timepoints of the human brain in a microarray dataset of the human brain from11. PCW: post-conception week, M: month, Y: year. Boxplot (in f): median (line), 25th and 75th percentiles (box), whiskers extend up to 1.5 times the interquartile range from the top (bottom) of the box to the furthest datum within that distance. Significance was calculated by comparing to background expression using one-sided Wilcoxon rank sum test. For detailed statistical information, see Supplementary Table 13. c-e) CH risk gene network connectivity in different layers of the prenatal human frontal neocortex. Analyzed transcriptomic dataset from13. c) VZ- and SVZi-specific CH risk gene interaction networks have the highest average connectivity per interaction. d-e) VZ (d) and SVZi (e) have significantly higher CH risk gene interaction network connectivity than expected by chance. The red line indicates the observed connectivity, and the gray histogram shows the null distribution from 1,000 permutations. P values were calculated by permutation tests (see Methods). f) Heatmap showing maximal expression of CH risk genes across different cell types of the developing human cortex. Analyzed transcriptomic dataset from12. g) Enrichment of CH risk genes in a prenatal human brain single-cell RNA sequencing data set from14. Purple square highlights lack of enrichment in choroid plexus cells. Choroid: choroid plexus, Glyc: glycolysis, IPC: intermediate progenitor cells, MGE: medial ganglionic eminence, OPC: oligodendrocyte precursor cells, RGC: radial glia cells. P values were calculated by hypergeometric test. h) Enrichment of CH risk genes in a postnatal mouse ventricular wall single-cell RNA sequencing data set from17. Purple square highlights lack of enrichment in ependymal cells. aNSC: actively dividing neural stem cells, TAC: transit amplifying cells, NB: neuroblasts, OPC: oligodendrocyte progenitor cells, COP: committed oligodendrocyte precursors. P values were calculated by hypergeometric test. i) Enrichment of CH risk genes in a prenatal mouse meninges single-cell RNA sequencing data set from18. P values were calculated by hypergeometric tests.

Extended Data Fig. 2 Gene co-expression network analysis of CH genetic risk.

a) Clustering dendrogram of genes showing module membership in colors. The y axis represents network distance as determined by 1-topological overlap (TO), where values closer to 0 indicate greater similarity of probe expression. Analyzed transcriptomic dataset from12. b-g) GO term enrichment analysis of gene co-expression modules that are enriched for CH risk genes. Significance was calculated by two-sided Fisher’s exact test. h-i) Co-expression network connectivity between CH and other developmental disorder risk genes. CH risk genes exhibit greater connectivity to cortical developmental disorder genes than to PCD genes. Significance was tested using one-sided Wilcoxon rank sum test by comparing to the reference group, CH-PCD.

Extended Data Fig. 3

Macrocephalic appearance of a hydrocephalic Trim71R595H/+ mouse compared to a WT control at P21.

Extended Data Fig. 4 Characterization of TRIM71 expression.

a) TRIM71 is minimally expressed in the adult human cortex. Analyzed single-nucleus RNA-sequencing data from12. b-c) RNAscope in situ hybridization of Trim71 in mouse embryonal carcinoma cells (b) or mouse Foxj1-expressing ependymal cell cultures (c) d) TRIM71 immunostaining in the WT mouse choroid plexus at P7.

Extended Data Fig. 5 Conditional knockout of Trim71 in embryonic NSCs by Nestin-Cre results in hydrocephalus in a subset of mice.

a) A subset of Nestin-Trim71fl/fl mice develop hydrocephalus with obvious macrocephaly at P21. b) Brain MRI demonstrates severe ventriculomegaly at P21 in a representative hydrocephalic Nestin-Cre;Trim71fl/fl mouse compared to a Trim71fl/fl control. 3D reconstructions of the ventricular system based on MRI scans are shown.

Extended Data Fig. 6 Mutant TRIM71 leads to reduced cell proliferation upon neural differentiation and an altered transcriptome.

a) Schematic of experimental paradigm of eFluor670 proliferation assay. Fluorescence intensity decreases by half upon every cell division. b,c) Representative histograms of eFluor670-labelled mESCs undergoing neural differentiation. Proliferation defects in mutant (Trim71R595H/+, Trim71R595H/R595H) (b) and Trim71 KO (c) mESC are reflected by slower loss of fluorescence intensity over time than that in WT or Trim71fl/fl control mESCs. d) Heatmap of the bulk RNA-sequencing showing gene expression profiles clustered in modules over mutant Trim71 genotypes.

Extended Data Fig. 7 Low levels of active caspase 3 (aCASP3) staining in the brains of control and Trim71 mutant mouse models.

a) aCASP3 staining in the neural tube neuroepithelia of WT, Trim71R595H/+, and Trim71R595H/R595H embryos at E9.5. b) aCASP3 staining in the cortices and lateral ventricles of WT and hydrocephalic Trim71R595H/+ mice at P0. c) aCASP3 staining in the cortices and lateral ventricles of Trim71fl/fl and hydrocephalic Nestin-Cre;Trim71fl/fl mice at P0.

Extended Data Fig. 8

H&E stained images of histological sections throughout the rostrocaudal extent of the midbrain cerebral aqueduct in P0 hydrocephalic Nestin-Trim71fl/fl mouse and a Trim71fl/fl control, demonstrating anatomical patency of the aqueduct in both genotypes.

Extended Data Fig. 9 Characterization of ependymal cilia and choroid plexus in hydrocephalic Trim71 mutant mice.

a) Coronal brain sections from control and hydrocephalic mice were stained for ciliary markers (acetyl-α-tubulin and ARL13B), ependymal cell markers (S100B and FOXJ1), and choroid plexus epithelial cell markers (E-Cadherin, OTX2).b-d) Immunostaining for molecular correlates of choroid plexus hypersecretion in WT controls and hydrocephalic Trim71R595H/+ P0 mice. Immunostaining of phosphorylated SLC12A2/NKCC1 (pSLC12A2) (b) and phosphorylated STK39/SPAK (pSTK39) (c) in the choroid plexi of a WT control and hydrocephalic Trim71R595H/+ P0 mouse. d) Immunostaining of SLC12A2/NKCC1 and STK39/SPAK in the choroid plexi of a WT control and hydrocephalic Trim71R595H/+ P0 mouse. e-f) Validation of OCT imaging platform to characterize ependymal cilia-driven CSF flow ex vivo. e). Representative flow polarity maps demonstrating bead trajectories (by temporal color coding) over time in an adult WT mouse brain explant in toxin-naive condition, with ciliobrevin, and after washout of toxin. Color bar represents color versus corresponding frame in the color-coded image. f) Quantitation of local CSF flow speed at the ventricular wall in brain explants from adult WT mouse brains in the different experimental conditions. g-i) CSF flow directionality in WT littermate controls and hydrocephalic Trim71R595H/+ mice at P7. g) Post-Gaussian processing CSF flow maps in a WT littermate control and hydrocephalic Trim71R595H/+ mice at P7. h,i) Quantitation of CSF flow directionality in WT littermate controls and hydrocephalic Trim71R595H/+ mice at P7. Directionality is represented as the distance between the start point and end point (d) divided by the bead pathway (d), see panel (i). Significance was tested by a two-sided paired t-test (f) or two-sided unpaired t-test (h): *: P<0.05, **: P<0.01, ns (not significant): P>0.05. Data represented as boxplots (f,h): median (line), 25th and 75th percentiles (box), whiskers go down to the smallest value and up to the largest, overlaid with individual data points. For detailed statistical information (f, h), see Supplementary Table 13.

Extended Data Fig. 10 TRIM71 CH-mutations lead to deregulation of Cdkn1a/p21 and Egr1 and loss of interaction to the NMD factor UPF1.

a,b) Representative immunoblots for the CLIP-qPCR assays in a) HEK293T cells and b) mESC. c-e) Protein levels of EGR1 and P21/CDKN1A in WT and mutant TRIM71 mESC. c) Representative immunoblots showing protein levels of EGR1 and P21/CDKN1A. d,e) Quantitation of EGR1 (d) and P21/CDKN1A (e) protein levels from immunoblots in (c). f-i) De-repression of CDKN1A 3′UTR in HEK293T cells overexpressing TRIM71 mutants and in Trim71 mutant mESCs. f) Schematic of luciferase assay to examine RNA target silencing by TRIM71 (CDKN1A as example). g) Luciferase reporter assay for the CDKN1A 3′UTR showing repression ability of the indicated TRIM71 constructs in HEK293T cells. Norm. RLU = normalized relative light units. h) Representative immunoblot showing TRIM71 construct overexpression for the CDKN1A-3′UTR luciferase assays in (g). i) Luciferase reporter assay for the CDKN1A 3′UTR showing repression ability of the indicated mESC line. j,k) CH-causing mutations impair TRIM71 binding to the NMD factor UPF1. Immunoblots show UPF1 enrichment upon co-precipitation with j) different Ig-tagged TRIM71 constructs transfected into HEK293T cells, namely Ig-Ctrl, Ig-TRIM71, Ig-ΔNHL6, Ig-R608H, and Ig-R796H or k) with endogenous FLAG-tagged TRIM71 and TRIM71-R595H in mESC. Statistical significance was tested by a two-sided, one-sample t-test (d, e, g, i): *: P<0.05, **: P<0.01, ***: P<0.001. Data represented as mean±s.e.m., overlaid with individual data points. For detailed statistical information (d, e, g, i), see Supplementary Table 13. Source data are provided.

Source data

Supplementary information

Reporting Summary

Supplementary Video 1

OCT imaging of cilia-generated CSF flow in a mouse adult ventricular explant in naive condition (top), with ciliobrevin toxin (middle) and after ciliobrevin toxin washout (bottom). The same ventricular explant was imaged for all three conditions.

Supplementary Tables 1–17

Source data

Source Data Fig. 7

Unprocessed immunoblots in Fig. 7.

Source Data Extended Data Fig. 10

Unprocessed immunoblots in Extended Data Fig. 10.

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Duy, P.Q., Weise, S.C., Marini, C. et al. Impaired neurogenesis alters brain biomechanics in a neuroprogenitor-based genetic subtype of congenital hydrocephalus. Nat Neurosci 25, 458–473 (2022). https://doi.org/10.1038/s41593-022-01043-3

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