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Vascular contributions to 16p11.2 deletion autism syndrome modeled in mice

Nature Neuroscience volume 23, pages 1090–1101 (2020)Cite this article

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Abstract

While the neuronal underpinnings of autism spectrum disorder (ASD) are being unraveled, vascular contributions to ASD remain elusive. Here, we investigated postnatal cerebrovascular development in the 16p11.2df/+ mouse model of 16p11.2 deletion ASD syndrome. We discover that 16p11.2 hemizygosity leads to male-specific, endothelium-dependent structural and functional neurovascular abnormalities. In 16p11.2df/+ mice, endothelial dysfunction results in impaired cerebral angiogenesis at postnatal day 14, and in altered neurovascular coupling and cerebrovascular reactivity at postnatal day 50. Moreover, we show that there is defective angiogenesis in primary 16p11.2df/+ mouse brain endothelial cells and in induced-pluripotent-stem-cell-derived endothelial cells from human carriers of the 16p11.2 deletion. Finally, we find that mice with an endothelium-specific 16p11.2 deletion (16p11.2ΔEC) partially recapitulate some of the behavioral changes seen in 16p11.2 syndrome, specifically hyperactivity and impaired motor learning. By showing that developmental 16p11.2 haploinsufficiency from endothelial cells results in neurovascular and behavioral changes in adults, our results point to a potential role for endothelial impairment in ASD.

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Fig. 1: Adult male 16p11.2df/+ mice exhibit altered neurovascular function.
Fig. 2: 16p11.2df/+ mice exhibit impaired endothelium-dependent vasodilation of pial arteries.
Fig. 3: Male 16p11.2df/+ mice exhibit delayed endothelial network maturation in the cerebral cortex.
Fig. 4: Effect of endothelium-specific 16p11.2 hemizygosity on neurovascular maturation in vivo.
Fig. 5: Brain ECs from P14 16p11.2df/+ males display reduced angiogenic activity.
Fig. 6: Transcriptional consequences of 16p11.2 haploinsufficiency in primary mouse brain ECs.
Fig. 7: 16p11.2-haplodeficient human-derived ECs display faulty angiogenic activity.
Fig. 8: Impact of developmental endothelium-specific 16p11.2 haploinsufficiency on adult mouse behavior.

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Data availability

Source data for the bulk RNA-seq experiments are available (GSE147790), and information on iPSC lines can be found in Supplementary Table 1. More details on control lines are available from the Stanford Lab (wstanford@ohri.ca). ANOVA tables are given as statistics source data files. All other data and protocols are available from the corresponding author upon reasonable request. Source data are provided with this paper.

Code availability

The custom scripts for blood vessel and neuronal quantifications, written in Python, are available on GitHub (https://github.com/chcomin/NatNeurosci2020) and from the Comin Lab (chcomin@gmail.com).

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Acknowledgements

We thank J.-C. Béïque, C.D. Harvey, P. Kaeser and C. Gu for their valuable comments on the manuscript; E. Hamel for generously sharing pressure myography equipment from her laboratory; D. Lagace, K. Ure and their assistant M. Barclay for training and guidance on behavioral assays; T. Portmann for advice on mouse genetics; C. Boisvert and K. Slodki for technical assistance on mouse husbandry and genotyping; A. Gagné and N. Vernoux for technical assistance on TEM; F. Xiao and M. Munkonda for training J. Ouellette on cell cycle analysis and tail-cuff plethysmography; L. Zhu for technical assistance; D.B. Stanimirovic for facilitating the collaboration with the National Research Council of Canada; A. Heinmiller for sharing equipment from the Fujifilm VisualSonics facility and for guidance on acoustic contrast imaging; S. Thompson for guidance on the marble-burying test; and C. Doré for helping organize experiments using control iPSC lines. For this work, B.L. was supported by start-up funds from the Ottawa Hospital Research Institute, by research grants from the Canadian Institutes of Health Research (CIHR) (grant no. 388805), the Scottish Rite Charitable Foundation of Canada (grant no. 17112), and the J. P. Bickell Foundation. C.H.C. thanks FAPESP (grant no. 15/18942-8). L.d.F.C. thanks CNPq (grant no. 307333/2013-2), FAPESP (grant no. 11/50761-2 and no. 2015/22308-2) and NAP-PRP-USP.

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Author notes

  1. These authors contributed equally: Julie Ouellette, Xavier Toussay.

Authors and Affiliations

  1. Neuroscience Program, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada

    Julie Ouellette, Xavier Toussay, Moises Freitas-Andrade, Cameron J. Morse, Peter Van Dyken & Baptiste Lacoste

  2. Department of Computer Science, Federal University of São Carlos, São Carlos, Brazil

    Cesar H. Comin

  3. São Carlos Institute of Physics, FCM-USP, University of São Paulo, São Paulo, Brazil

    Luciano da F. Costa

  4. Regenerative Medicine Program, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada

    Mirabelle Ho, William L. Stanford & Duncan J. Stewart

  5. Montreal Neurological Institute, McGill University, Montréal, Québec, Canada

    María Lacalle-Aurioles & Sylvain Baillet

  6. National Research Council of Canada, Human Health and Therapeutics, Ottawa, Ontario, Canada

    Qing Yan Liu & Sonia Leclerc

  7. Department of Biochemistry Microbiology and Immunology, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada

    Qing Yan Liu

  8. Digital Technologies, National Research Council of Canada, Ottawa, Ontario, Canada

    Youlian Pan & Ziying Liu

  9. Kidney Research Center, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada

    Jean-François Thibodeau, Christopher R. Kennedy & Dylan Burger

  10. FUJIFILM VisualSonics, Toronto, Ontario, Canada

    Melissa Yin

  11. Axe Neurosciences, Centre de recherche du CHU de Québec, Université Laval, Québec, Québec, Canada

    Micael Carrier & Marie-Ève Tremblay

  12. Department of Cellular and Molecular Medicine, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada

    Christopher J. Bergin, Christopher R. Kennedy, Yannick D. Benoit, William L. Stanford, Dylan Burger, Duncan J. Stewart & Baptiste Lacoste

  13. University of Ottawa Brain and Mind Research Institute, Ottawa, Ontario, Canada

    Baptiste Lacoste

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Contributions

J.O., X.T., B.L., M.H., M.L.-A., S.L., M.Y., J.-F.T., C.J.M., P.V.D., M.F.-A., M.C., Y.D.B. and C.J.B. performed experiments. J.O., X.T., M.H., C.H.C., L.d.F.C., M.L.-A., C.J.M., J.-F.T., P.V.D., M.F.-A. and C.J.B. analyzed the data/images in a blinded manner. Q.Y.L., S.L., Y.P., Z.L., Y.D.B. and B.L. generated and/or analyzed transcriptomic data. S.B. provided expertise for the ECoG data analysis. W.L.S. provided healthy donor iPSC lines and expertise in stem cell research. D.J.S. (supervisor of M.H.) provided expertise in endothelial differentiation of iPSCs. B.L. conceived and led the project, designed experiments and wrote the manuscript from a draft produced by J.O., with input from X.T., M.F.-A., M.L.-A., M.-È.T., D.B., C.R.K., S.B., Y.D.B., D.J.S. and W.L.S.

Corresponding author

Correspondence to Baptiste Lacoste.

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The authors declare no competing interests.

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Peer review information Nature Neuroscience thanks Anusha Mishra and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Neurovascular parameters in 16p11.2df/+ and WT mice at P14 and P50.

a, CBF assessment by LDF in 16p11.2df/+ and WT females at P14 and P50. Only falling slope appeared affected by genotype in females at P14. b, Additional representative images and a diagram for contrast imaging method, showing the region of interest (ROI, dotted lines) before (pre.) and after (post.) i.v. injection of microbubbles. The graph on the right shows identical ROI size in all animals. c, Additional CBF parameters in 16p11.2df/+ and WT males versus females. d, LDF traces (mean ± s.e.m.) obtained before, during, and after whisker stimulation in all mice (regrouped by genotype). e, Mean systolic blood pressure and heart rate measured over 5 days at P50 using tail cuffs. WT, Wild-Type. Data are whisker boxes (min to max, center line indicating median) in a and c, or mean with individual values in b and e. Traces in a and d are mean ± s.e.m. (n = 4-8 animals per group). *P < 0.05 (two tailed Mann-Whitney test). ♂: males; ♀: females.

Extended Data Fig. 2 Cerebrovascular and electrophysiological parameters in male and female 16p11.2df/+ and WT mice at P14 and P50.

a, LDF recording (Tissue perfusion units, mean ± s.e.m.) of resting state CBF over the primary somatosensory cortex from anesthetized mice, averaged over 40 sec. b, Quantification and comparison of resting state CBF using LDF in all groups of mice. c,d, ECoG recordings in the primary somatosensory cortex from P14 male (c), and P50 female (d) 16p11.2df/+ and WT mice. In c and d: Left, Representative power spectral traces of low-frequency bands (n = 4-5 animals per group; 6 stimulations per animal). Right, Average absolute power in Delta (1-4 Hz), Theta (4-8 Hz), Alpha (8-13 Hz), Beta (13-30 Hz), Low Gamma (35-55 Hz) and High Gamma (65-100 Hz) frequency bands at resting-state (upper panel) and during stimulation (lower panel). Data (right) are mean with individual values (n = 4-5 animals per group; 6 stimulations per animal). Data are mean ± s.e.m. in a, whisker boxes (min to max, center line indicating median) in b, or mean with individual values in c,d (right) (n = 4-6 animals per group). **P < 0.01, ***P < 0.001 (2-way ANOVA and Tukey’s post-hoc test in b).

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Extended Data Fig. 3 Ex vivo vascular reactivity (VR) of middle cerebral and mesenteric arteries from 16p11.2df/+ and WT mice at P50.

a, Schematic representation of cellular and molecular VR mechanisms. b, Upper panels, Wire myography of mesenteric arteries ex vivo confirming 16p11.2 deletion-induced endothelial dysfunction. Females and males display a similar endothelial-dependent deficit, but normal VSMC response. Lower panels, pD2 values obtained from the dose-response curves from male and female mice. c, pD2 values obtained from dose-response curves of male and female middle cerebral arteries (see Fig. 2). ACh, acetylcholine; L-NNA, NG-Nitro-L-arginine; PE, phenylephrine; SNP, sodium nitroprusside; VSMC, vascular smooth muscle cell; WT, Wild-Type. Data are mean ± s.e.m. in b (upper panel), or whisker boxes (min to max, center line indicating median) in b (lower panel) and c (n = 5-7 animals per sex group). *P < 0.05 (2-way repeated measure ANOVA and Tukey’s post-hoc test in b).

Extended Data Fig. 4 Postnatal neurovascular maturation in the cerebral cortex of 16p11.2df/+ and WT mice.

a–c, Postnatal developmental profile of cerebral cortex endothelial networks in 16p11.2df/+ and WT males (cortical layers where most significant differences were found). d-i, Postnatal developmental profile of cerebral cortex endothelial networks in 16p11.2df/+ and WT females. j, Sample image of the computational approach used to delineate ROIs in the cortex to quantify neuronal density (see methods for details). k, Quantification of neuronal density in the parietal (that is, somatosensory) cortex of female mice following immunostaining for neuronal markers NeuN and TBR1. l, Vascular endothelial growth factor-A (VEGF-A) levels measured by E.L.I.S.A. in protein extracts from cerebral cortex micro-dissected at P14 or P50 in male and female mice. WT, Wild-Type. Data are mean ± s.e.m. in a-i and k, or mean with individual values in l (n = 3-6 animals per group). *P < 0.05 (two tailed Mann-Whitney test). #P < 0.05, ###P < 0.001 (2-way ANOVA and Sidak’s post-hoc test).

Extended Data Fig. 5 Morphology of the neurovascular unit in male 16p11.2df/+ and WT mice at P14 and P50.

Immunohistochemical analysis of vascular smooth muscle cells, VSMCs (a, SMA), pericytes (b, PDGFR-β), astrocytes (c, Aldh1l1-eGFP) and microglia (d, Iba1) in the cerebral cortex. a, Endothelial coverage by VSMCs measured in the anterior, parietal and occipital cortex. b, Pericyte density and endothelial coverage measured in the anterior, parietal and occipital cortex. Endothelial marker CD31 was used in a and b to stain vessels. c, Astrocyte density and surface coverage measured in the anterior, parietal and occipital cortex of mice expressing eGFP under the control of the pan-astrocytic Aldh1l1 promotor. d, Microglia density and surface coverage measured in the anterior, parietal and occipital cortex. e, Top, Transmission electron micrograph showing astrocytic endfeet (red-pseudocolored) surrounding a brain capillary. Bottom, Quantification of average endfoot size (left) and endothelial coverage ratio by endfeet (right). f, Transmission electron micrographs showing pericytes (pink-pseudocolored) within the basement membrane around brain endothelial cells (green-pseudocolored). Images are representative of experiments repeated in 4 male mice per group, with similar results. Normal astrocyte coverage and pericyte attachment were observed in 16p11.2df/+ mice. A, astrocytes; L, lumen; P, pericyte; WT, Wild-Type. All data are mean with individual values (n = 3-7 animals per group). *P < 0.05 (two tailed Mann-Whitney test in c).

Extended Data Fig. 6 Additional information on neurovascular features in conditional 16p11.2ΔEC mutants and Cdh5-Cretg/+ controls at P50.

a, Quantification of neuronal density in the parietal (that is, somatosensory) cortex of P50 males and females following immunostaining for neuronal markers NeuN and TBR1. b, Quantification of cortical thickness and layering from micrographs of DAPI-stained brain sections from males and females. No difference was evidenced between 16p11.2ΔEC and control mice. c, Normal mean systolic blood pressure and heart rate in 16p11.2ΔEC as measured by tail cuffs. d, ECoG recordings in the primary somatosensory cortex from P50 female 16p11.2ΔEC and control mice. Top panels, representative power spectral traces of low-frequency bands. Bottom graphs, average absolute power in Delta (1-4 Hz), Theta (4-8 Hz), Alpha (8-13 Hz), Beta (13-30 Hz), Low Gamma (35-55 Hz) and High Gamma (65-100 Hz) frequency bands at resting-state (upper graphs) and during stimulation (bottom graphs). Data are mean ± s.e.m. in a, whisker boxes (min to max, center line indicating median) in b, or mean with individual values in c and d (n = 4-8 animals per group). #P < 0.05 (2-way ANOVA and Sidak’s post-hoc test in a). *P < 0.05 (Mann-Whitney test in c).

Extended Data Fig. 7 Characterization of primary mouse cerebral cortex ECs (cECs) from male WT and 16p11.2df/+ mice.

a, Representative images and quantifications of immunocytochemical staining for cEC-specific markers GLUT-1, eNOS and VE-Cadherin, showing no difference between WT and mutant cECs isolated at P14 (blue: DAPI). b, Assessment of apoptosis in P14 cEC cultures. The Caspase-3/7 green assay revealed normal apoptotic rates in 16p11.2df/+ cECs. c, qPCR validation on cEC RNA using mouse VEGFR-2, CD31 and eNOS as markers (a no reverse transcriptase control was used as negative control). d, Assessment of endothelial gene enrichment using RNAseq data normalized to a publicly-available database from Dr. Ben A. Barres lab, Stanford University, USA (Zhang et al. 2014, PMID 25186741; http://www.brainrnaseq.org/). e, Assessment of neuronal contamination using RNAseq data (as in d). A very low level of contamination was achieved. Examples given are from cortical endothelial cells (cECs) isolated from male mice at P14. f, Confirmation of cEC 16p11.2 haploinsufficiency by RNAseq. Mapping of fold change (FC) to 7qF3 locus genes confirms a ~50% decrease in gene expression levels at both P14 and P50. Data are mean ± s.e.m in a (VE-Cadh.) and c,d,e, whisker boxes (min to max, center line indicating median) in a (eNOS, GLUT1), or mean with individual values in b. CTL, control; WT, Wild-Type. For RNAseq, n = 3-4 biological replicates per group (2 mice per replicate).

Extended Data Fig. 8 In vitro network formation assay using primary cECs from P14 and P50 male mice.

a, In vitro network formation assay using primary cECs from P50 brains to assess vascular network formation and remodeling over 48 hrs in a growth factor-reduced Matrigel® (EGF < 0.5 ng/mL; PDGF < 5 pg/mL; IGF-1 5 ng/mL; TGF-β 1.7 ng/mL). No significant difference was quantified between 16p11.2df/+ and WT cECs. b, Assessment of cell proliferation using cell cycle analysis with cECs from P50 brains. The proportion of cells in G2/S (proliferation) or G1 (growth) phases was identical between 16p11.2df/+ and WT cECs. c, Cultured P14 cECs were seeded in a growth-factor supplemented Matrigel® (EGF: 0.7 ng/mL; PDGF 12 pg/mL; IGF1 16 ng/mL; TGFβ 2.3 ng/mL). Impaired angiogenic activity of 16p11.2df/+ of cECs was only partly rescued in these conditions. Data are mean ± s.e.m. in a and c, or whisker boxes (min to max, center line indicating median) in b (n = 4-5 animals per group). *P < 0.05 (2-way repeated measure ANOVA and Sidak’s post-hoc test).

Extended Data Fig. 9 Human iPSC lines used to derive endothelial cells, and the quality controls.

a, Representative images of cell morphology from culture steps (D=day) involved in differentiating human iPSC into human-induced endothelial cells (hiECs). Images are representative of 3 experiments repeated independently with similar results. b, Representative flow cytometric plots of MAC-selected CD144- positive cells from both control (healthy) and 16p11.2 individuals, demonstrating similarly high expression of endothelial markers CD31 and CD34. Conversely, CD144-negative hiECs show negligible expression of endothelial markers. Flow cytometric plots displayed are representative of 4 experiments repeated independently with similar results. c, Left, Sample images of immunocytochemical staining for endothelial marker VE-Cadherin in hiEC cultures. Right, Quantification of VE-Cadherin staining intensity across cell-cell junctions (total of 100 junctions/genotype) showing normal endothelial differentiation using 16p11.2 deletion iPSCs. d, Assessment of apoptotic rates in cell culture using a Caspase3/7 green assay shows no difference between control and 16p11.2 DEL hiECs. e, Assessment of proliferation in cell culture using an EdU incorporation assay shows no difference between control and 16p11.2 DEL hiECs. f, Quantification of core endothelium-enriched genes using ClariomTM S shows no differences between control and 16p11.2 DEL hiECs. g, Quantification of 16p11.2 locus genes using ClariomTM S microarray confirms hemizygosity of 16p11.2 DEL hiECs compared to control hiECs. DEL, deletion. Data are mean ± s.e.m. in c, f and g, whisker boxes (min to max, center line indicating median) in d, or mean with individual values in e (n = 3 cell lines per group). **P < 0.01, ***P < 0.001 (2-way ANOVA and Tukey’s post-hoc test).

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Extended Data Fig. 10 Additional behavioral analysis of constitutive and conditional mutant mice and their controls.

a, b, Left, Assessment of home cage activity in the beam break test for combined 16p11.2ΔEC and control littermates (a), or combined male and female 16p11.2df/+ and WT mice (b). Right, First 12hrs of habituation (from testing day 1) in the beam break test for male and female 16p11.2ΔEC and control littermates (a), or 16p11.2df/+ and WT mice (b). c,d, Assessment of motor learning/coordination in the rotarod test for combined male and female 16p11.2df/+ and WT mice (c), or 16p11.2ΔEC and control littermates (d). e, The marble burying test revealed a phenotype for combined sexes in 16p11.2ΔEC mice (right), but not 16p11.2df/+ mice (left). f, The novel object recognition test revealed a phenotype for combined sexes in 16p11.2df/+ mice (left), but not for 16p11.2ΔEC mice (right). Data are mean ± s.e.m. in a-d, or mean with individual values in e and f (n = 9-18 mice per sex group). *P < 0.05, **P < 0.01, ***P < 0.001 (2-way repeated measure ANOVA and Sidak’s post-hoc test in a-c; Mann-Whitney test in e and f). ♂: males; ♀: females.

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Ouellette, J., Toussay, X., Comin, C.H. et al. Vascular contributions to 16p11.2 deletion autism syndrome modeled in mice. Nat Neurosci 23, 1090–1101 (2020). https://doi.org/10.1038/s41593-020-0663-1

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