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Meningeal lymphatics affect microglia responses and anti-Aβ immunotherapy

Abstract

Alzheimer’s disease (AD) is the most prevalent cause of dementia1. Although there is no effective treatment for AD, passive immunotherapy with monoclonal antibodies against amyloid beta (Aβ) is a promising therapeutic strategy2,3. Meningeal lymphatic drainage has an important role in the accumulation of Aβ in the brain4, but it is not known whether modulation of meningeal lymphatic function can influence the outcome of immunotherapy in AD. Here we show that ablation of meningeal lymphatic vessels in 5xFAD mice (a mouse model of amyloid deposition that expresses five mutations found in familial AD) worsened the outcome of mice treated with anti-Aβ passive immunotherapy by exacerbating the deposition of Aβ, microgliosis, neurovascular dysfunction, and behavioural deficits. By contrast, therapeutic delivery of vascular endothelial growth factor C improved clearance of Aβ by monoclonal antibodies. Notably, there was a substantial overlap between the gene signature of microglia from 5xFAD mice with impaired meningeal lymphatic function and the transcriptional profile of activated microglia from the brains of individuals with AD. Overall, our data demonstrate that impaired meningeal lymphatic drainage exacerbates the microglial inflammatory response in AD and that enhancement of meningeal lymphatic function combined with immunotherapies could lead to better clinical outcomes.

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Fig. 1: Compromised meningeal lymphatic function in 5xFAD mice limits brain Aβ clearance by chimeric mAducanumab and modulates the microglial and neurovascular responses.
Fig. 2: Combining mVEGF-C with immunotherapy reprograms the hippocampal transcriptional profile and shapes the microglial and neurovascular responses in aged APPswe mice.
Fig. 3: Gene-set analysis uncovers a link between impaired meningeal lymphatics and microglial activation in AD.

Data availability

Source data files depicting the quantification values mentioned in the text or plotted in graphs shown in Figs. 1, 3 and Extended Data Figs. 15, 79, and the gene lists used for gene-set analysis in Supplementary Tables 3, 6 are available in the online version of this paper. New RNA-seq datasets have been deposited online in the Gene Expression Omnibus (GEO database) under the accession number GSE141917. Previously published RNA-seq datasets can be found under the accession numbers GSE99743 and GSE104181. Source data are provided with this paper.

Code availability

Custom code used to analyse the RNA-seq data and datasets generated and/or analysed in the current study are available from the corresponding authors upon request.

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Acknowledgements

We thank S. Smith for editing the manuscript and S. Blackburn and N. Al-Hamadani for animal colony maintenance. This work was supported by grants from the National Institutes of Health/National Institute on Aging (AG034113 and AG057496), PureTech Health, the Cure Alzheimer’s Fund and the Ed Owens Family Foundation to J.K.; RF1AG053303 and RF1AG058501 to C.C.; AG057777 and AG067764 to O.H.; and AG062734 to C.M.K. O.H. is an Archer Foundation Research Scientist. We thank all members of the Kipnis laboratory for their comments during discussions of this work. We acknowledge the staff of the Neuropathology Cores and other personnel of the Charles F. and Joanne Knight Alzheimer Disease Research Center (P30 AG066444, P01AG026276, P01AG03991). Data collection and sharing for this project were supported by The Dominantly Inherited Alzheimer’s Network (DIAN, UF1AG032438) funded by the National Institute on Aging (NIA), the German Center for Neurodegenerative Diseases (DZNE), Raul Carrea Institute for Neurological Research (FLENI), with partial support by the Research and Development Grants for Dementia from Japan Agency for Medical Research and Development, AMED, and the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI). This manuscript has been reviewed by DIAN Study investigators for scientific content and consistency of data interpretation with previous DIAN Study publications. We acknowledge the altruism of the participants and their families and contributions of the Knight ADRC and DIAN (see full list of DIAN consortium members in Supplementary Notes) research and support staff at each of the participating sites for their contributions to this study.

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Contributions

S.D.M. designed and performed the experiments, analysed and interpreted the data, created the figures and wrote the manuscript; Z.P. optimized experimental techniques, performed experiments, analysed data and participated in manuscript writing; T.D. performed the mouse scRNA-seq data analyses, integrated analysis of mouse and human RNA-seq data and participated in methods writing; L.B. performed the human brain single-nucleus RNA-seq data analysis, integrated analysis of mouse and human RNA-seq data and participated in methods writing; F.G.F. performed the integrative gene-set, genetic variant and AD phenotype and risk analyses; M.W. was involved in the bulk RNA-seq and mass cytometry data analyses and participated in methods writing; H.J. synthesized the mouse chimeric Aducanumab and control antibodies; C.D.K. contributed to bulk RNA-seq data analysis; K.A.d.L., J.H., A.L., D.H.G. and A.F.S. assisted in experiments and data analysis; S.O.-G. and E.F. assisted in bulk RNA-seq experiments; N.D., T.K., M.G.M. and W.B. and I.S. assisted with animal genotyping, experiments and blinded data analyses and quantification; S.S.R. supervised the bulk RNA-seq experiments and participated in manuscript writing; B.A.B., C.M.K., R.J.P., M.F. and J.P.C. were involved in the collection and analysis of human brain single-nucleus RNA-seq data and critical review of the manuscript; D.M.H. provided resources and was involved in experimental design, data interpretation and manuscript writing; C.C. supervised and interpreted the integrative gene-set, genetic variant and AD phenotype and risk analyses and participated in manuscript writing; O.H. supervised and interpreted the human brain single-nucleus RNA-seq data analysis and participated in manuscript writing; J.K. designed the experiments, provided intellectual contributions, oversaw data analysis and interpretation and wrote the manuscript.

Corresponding authors

Correspondence to Sandro Da Mesquita or Jonathan Kipnis.

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Competing interests

J.K. is a member of a scientific advisory group for PureTech. J.K., S.D.M. and A.L. hold patents and patent applications related to the findings described herein. D.M.H. is an inventor on a patent for anti-Aβ antibodies licensed to Eli Lilly by Washington University. D.M.H. and H.J. are inventors on a patent for anti-apoE antibodies licensed to NextCure. D.M.H. and H.J. are listed as inventors on a patent licensed by Washington University to C2N Diagnostics on the therapeutic use of anti-tau antibodies. D.M.H. co-founded and is on the scientific advisory board of C2N Diagnostics. C2N Diagnostics has licensed certain anti-tau antibodies to AbbVie for therapeutic development. D.M.H. is on the scientific advisory board of Denali and consults for Genentech, Merck, and Cajal Neuroscience. C.C. receives research support from Biogen, EISAI, Alector and Parabon. The funders of the study had no role in the collection, analysis, or interpretation of data, in the writing of the manuscript, or in the decision to submit the paper for publication. C.C. is a member of the advisory board of Vivid Genetics, Halia Therapeutics and ADx Healthcare. J.P.C. has served on a medical advisory board for Otsuka Pharmaceuticals. The authors declare no other competing interests.

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Extended data figures and tables

Extended Data Fig. 1 Morphological assessment and functional enrichment analysis of differentially expressed genes show accelerated meningeal lymphatic dysfunction in 5xFAD mice.

a, Representative images of meningeal whole mounts from 5xFAD mice at 5–6 and 13–14 months of age, stained for CD31 (blue), LYVE-1 (green) and Aβ (red, stained with the D54D2 antibody; scale bar, 2 mm; inset scale bar, 500 μm). b, Scheme depicting the compartmentalization of the meningeal whole mount for quantification of LYVE-1 and Aβ coverage. ce, Graphs showing the coverage by LYVE-1+ vessels and Aβ as a percentage of the region of interest (% of ROI) at the superior sagittal sinus (c; SSS),) transverse sinus and confluence of sinuses (d; TS/COS), and petrosquamosal and sigmoid sinuses (e; PSS/SS). Results in ce are presented as mean ± s.e.m.; n = 8 per group; two-way ANOVA with Holm–Sidak’s multiple comparisons test (for LYVE-1+ vessels) and two-tailed unpaired Student’s t-test (for Aβ coverage); data are from two independent experiments. f, Lymphatic endothelial cells (LECs) were isolated from the brain meninges of male 5xFAD mice and wild-type littermate controls at 6 months of age, and total RNA was extracted and sequenced. g, PCA plot showing segregation between wild-type (blue) and 5xFAD (purple) meningeal LEC transcriptomes. h, Heat map of top 50 differentially expressed genes in 5xFAD meningeal LECs at 6 months of age. i, Gene-sets obtained by functional enrichment of differentially expressed genes in meningeal LECs from 5xFAD mice. j, k, Exocytosis (GO: 0006887) and phospholipase D signalling pathway (KEGG: mmu04072) gene-sets obtained by functional enrichment analysis, with corresponding differentially expressed genes. gk, n = 3 per group; individual RNA samples result from LECs pooled from 10 meninges over 3 independent experiments; the Benjamini–Hochberg correction was used to adjust the associated P values in i (Padj < 0.05); functional enrichment of differential expressed genes in i was determined with Fisher’s exact test; colour scale bars in h and k represent expression values for each sample as standard deviations from the mean across each gene. Source data

Extended Data Fig. 2 Meningeal immune cell profiling by mass cytometry in 5xFAD mice at 5–6 and 11–12 months.

a, Meningeal single-cell suspensions were obtained from male 5xFAD mice at 5–6 months and 11–12 months and processed for mass cytometry. Representative mass cytometry dot plots depicting gating strategy used to select CD45+ live cells used in further high-dimensional analysis. b, Heat maps of the median marker expression values for each immune cell cluster identified using Rphenograph. Median marker expression values are indicated by colour intensity depicted in the scale bar. c, t-Distributed stochastic neighbour embedding-based visualization (viSNE) plots showing unsupervised clustering of CD45+ live immune cells. d, Number of CD45+ live meningeal leucocytes at 5−6 (orange) and 11−12 (purple) months in 5xFAD mice. e, Numbers of different meningeal immune cells showing a statistically significant increase in B cells, CD4+ T cells 1, CD8+ T cells, type 3 innate lymphoid cells (ILC3s) and undefined cells in the meninges of 5xFAD mice at 11–12 months of age. Data are representative of a single experiment; results in d and e are presented as mean ± s.e.m.; n = 7 per group; two-tailed unpaired Student’s t-test. Source data

Extended Data Fig. 3 Compromising meningeal lymphatic function in 5xFAD mice limits brain Aβ clearance by mAb158 and modulates neuritic dystrophy, microglial activation and fibrinogen levels.

ae, Adult 2-month-old male wild-type mice were injected with 5 μl visudyne (i.c.m.) followed by a transcranial photoconversion step (vis/photo) to ablate meningeal lymphatic vessels at the dorsal meninges. Control mice were injected with visudyne without photoconversion (vis). One week later, each mouse was injected with 5 μl of a suspension of fluorescent microspheres (1 μm in diameter) into the CSF and 15 min later the lymphatic vessel afferent to the deep cervical lymph node (dCLN) was imaged by live in vivo fluorescence stereomicroscopy. a, Representative images of skull caps with attached meningeal layers showing microspheres (blue) and lymphatic vessels stained for LYVE-1 (green) around the confluence of sinuses (COS) and transverse sinus (TS) at the dorsal meninges or around the sigmoid (SS) and petrosquamosal (PSS) sinuses at the basal meninges (scale bars, 500 μm). b, c, Graphs showing total length of LYVE-1+ vessels (in mm) and number of branching points in lymphatics at the dorsal (b) and basal (c) meninges. Results in b, c are presented as mean ± s.e.m.; n = 10 per group; two-tailed unpaired Student’s t-test; data are representative of two independent experiments. d, Representative frames showing microspheres flowing through the lymphatic vessel afferent to the dCLN, or cumulative sphere tracking (for 20 s), in mice with intact or ablated meningeal lymphatic vessels. e, Quantification of microsphere flow (number of microspheres per minute) in mice from each group. Results in e are presented as mean ± s.e.m.; n = 11 in vis group and n = 14 in vis/photo group; two-tailed unpaired Student’s t-test; data are from two independent experiments. f, Adult 3- to 3.5-month-old male 5xFAD mice were injected with visudyne with or without photoconversion as in a. Upon recovery, mice received intraperitoneal (i.p.) injections of mAb158 (a mouse antibody against Aβ protofibrils) or the control mouse IgG (mIgG) antibodies, each at a dose of 40 mg kg−1. Antibodies were injected weekly for four weeks. Additional steps of meningeal lymphatic vessel ablation or control interventions were followed by four weekly injections with antibodies. Mice were tested in the open field and Morris water maze (Extended Data Fig. 4). g, Representative images of brain sections from 5xFAD mice stained for Aβ (red, stained with the D54D2 antibody) and LAMP1 (green; scale bars, 1 mm). hl, Graphs showing number of Aβ plaques per mm2 of brain section (h), average size of Aβ plaques (μm2) in mAb158 cohort (i), average size of Aβ plaques (μm2) in mAducanumab cohort (j; related to Fig. 1a-e), coverage by Aβ plaques (k) and coverage by LAMP1+ dystrophic neurites (l; as percentage of brain section) in each group. m, Representative images of the brain cortex stained for Aβ (blue, stained with Amylo-Glo), fibrinogen (grey), IBA1 (green) and CD68 (red; scale bar, 100 μm). nq, Graphs showing coverage by IBA1+ cells (n; percentage of field), number of peri-Aβ plaque IBA1+ cells (o), percentage of IBA1 occupied by CD68 (p) and fibrinogen coverage (q; percentage of field) in each group. Data in fq are representative of a single experiment; results in hl and nq are presented as mean ± s.e.m.; n = 9 in each group; in h, i, j, l and nq, two-way ANOVA with Holm–Sidak’s multiple comparisons test; in k, two-tailed unpaired Student’s t-test. Source data

Extended Data Fig. 4 Meningeal lymphatic dysfunction leads to anxiety-like behaviour and worsened spatial learning and memory in 5xFAD mice.

a, Adult 5xFAD mice with intact or ablated meningeal lymphatics and treated with mAducanumab (mAdu) or control mIgG antibodies (see Fig. 1 for experimental scheme and more results) were tested in the open field arena and in the Morris water maze. bd, Performance in open field arena: total distance travelled (b; in centimetres), velocity (c; in centimetres per second) and percentage of time in the centre of the open field arena (d; percentage of total time). eg, Performance in Morris water maze: latency to platform in acquisition (e; in seconds), percentage of time in the platform quadrant in the probe trial (f) and latency to platform in reversal (g, in seconds). Data in ag are from a single experiment; results in bg are presented as mean ± s.e.m.; n = 10 (vis) and n = 9 (vis/photo); two-way ANOVA with Holm–Sidak’s multiple comparisons test in bd and f; repeated measures two-way ANOVA with Tukey’s multiple comparisons test in e and g; statistically significant differences between groups in days 3 and 4 of the Morris water maze test are indicated as D3 and D4, respectively. h, Adult 5xFAD mice with intact or ablated meningeal lymphatics and treated with mAb158 or control mIgG antibodies (see Extended Data Fig. 3f–q for experimental scheme and more results) were tested in the open field arena and in the Morris water maze. ik, Performance in open field arena: total distance (i; in centimetres), velocity (j; in centimetres per second) and percentage of time in the centre of the open field arena (k; percentage of total time). ln, Performance in Morris water maze: latency to platform in acquisition (l, in seconds), percentage of time in the platform quadrant in the probe trial (m) and latency to platform in reversal (n; in seconds). Data in hn are from a single experiment; results in in are presented as mean ± s.e.m.; n = 9 in each group; two-way ANOVA with Holm–Sidak’s multiple comparisons test in ik and m; repeated measures two-way ANOVA with Tukey’s multiple comparisons test in l and n; statistically significant differences between groups in days 3, 4 and 7 of the Morris water maze test are indicated as D3, D4 and D7, respectively. Source data

Extended Data Fig. 5 Meningeal lymphatic vessel ablation precludes brain Aβ plaque clearance by mAb158 administered into the CSF.

a, Adult 4- to 4.5-month-old male 5xFAD mice were injected (i.c.m.) with visudyne (5 μl) plus photoconversion (vis/photo) or visudyne without photoconversion (Vis). One week later, 5 μl mAb158 antibodies or the same volume of the control mouse IgG (mIgG) antibodies were directly injected into the CSF (i.c.m.), both at 1 μg μl−1. Injections with antibodies were repeated two weeks later. Additional steps of meningeal lymphatic vessel ablation or control interventions were followed by two more i.c.m. injections with antibodies, as shown. b, Representative images of meningeal whole mounts stained for CD31 (blue), LYVE-1 (green) and Aβ (red, stained with the D54D2 antibody; scale bar, 2 mm). c, Coverage by Aβ as a percentage of the meningeal whole mount. d, Representative images of brain sections from 5xFAD mice stained for Aβ (red, stained with the D54D2 antibody) and with DAPI (blue; scale bar, 2 mm). eg, Graphs showing number of Aβ plaques per mm2 of brain section (e), average size of Aβ plaques (f; μm2) and total coverage of Aβ plaques (g; percentage of brain section) in each group. h, Representative inset showing an example of a Prussian blue focus in a brain tissue section of a 5xFAD mouse (scale bar, 100 μm). i, Quantification of Prussian blue foci per brain section in each group. Data in ai are representative of two independent experiments; results in c, eg and i are presented as mean ± s.e.m.; n = 8 in vis + mIgG, vis + mAb158 and vis/photo + mIgG, n = 7 in vis/photo + mAb158; two-way ANOVA with Holm–Sidak’s multiple comparisons test. j, 5xFAD mice (5 months old) with intact or ablated meningeal lymphatic vasculature were injected (i.c.m.) with 5 μl mAb158 (at 1 μg μl−1). One hour later, mice were transcardially perfused and the brains were collected for assessment of mAb158 linked to Aβ in blood vasculature or Aβ plaques. Images of ten different regions of the brains of 5xFAD mice from each group showing blood vessels stained for CD31 (blue), Aβ plaques (green, stained with Amylo-Glo) and mAb158 (red; scale bar, 200 μm). k, Colocalization between mAb158 and CD31 (percentage of total CD31 coverage) in each brain region (1 to 10) or presented as the average of all regions. l, Colocalization between mAb158 and Amylo-Glo (percentage of total Amylo-Glo-stained Aβ plaques) in each brain region (1 to 10) or presented as the average of all regions. Data in jl are from a single experiment; results in k and l are presented as mean ± s.e.m.; n = 5 per group; two-way ANOVA with Holm–Sidak’s multiple comparisons test (for comparisons between groups in each brain region) and two-tailed unpaired Student’s t-test (for comparisons between the two groups). Source data

Extended Data Fig. 6 Effects of meningeal lymphatic vessel ablation and mAducanumab immunotherapy on the microglial and blood endothelial cell transcriptomes in 5xFAD mice.

a, Representative flow cytometry dot plots showing gating strategy used to sort (and enrich for) live (DAPI) singlets that were CD45+CD11b+Ly6G (macrophages/microglia), CD45CD11bCD31+ (blood endothelial cells) and CD45CD11bCD13+CD31 (mural cells). b, c, Representations of tSNE plots highlighting the brain cells identified by scRNA-seq discriminated by group (b) or type (c). d, Dot plot depicting the average scaled expression levels of specific genes (x-axis) used to identify the brain cell populations, as well as the percentage of cells that expressed those genes within each population; choroid plexus blood endothelial cells (cpBECs), border-associated macrophages (BAMs), arterial BECs (aBECs), capillary BECs (cBECs) and venous BECs (vBECs). e, Heat map showing expression levels of genes involved in the transition from homeostatic to Trem2-independent and Trem2-dependent disease-associated microglia phenotypes in the different groups. f, Violin plots showing the expression levels of the homeostatic P2ry12, Tmem119, Cx3cr1, Selplg and Hexb genes, and disease-associated microglial Apoe, Lyz2, Fth1, B2m, Timp2, H2-d1, Axl, Cst7, Spp1 and Lpl genes in each group. g, Top ten Gene Ontology terms obtained after analysing genes that were significantly downregulated in microglia from the vis/photo + mIgG group compared to the vis + mIgG group. h, Volcano plot with significantly downregulated (in blue) and upregulated (in orange) genes after comparing the transcriptomes of cBECs from the vis/photo + mIgG and vis + mIgG groups. i, j, Top ten Gene Ontology terms obtained after analysing significantly upregulated (i) or downregulated (j) genes in cBECs from the vis/photo + mIgG group, when compared to the vis + mIgG group. kn, Volcano plots, with significantly downregulated (blue) and upregulated (orange) genes, and top ten Gene Ontology terms (using upregulated genes) obtained after comparing the transcriptomes of aBECs (k, l) and vBECs (m, n) from the vis/photo + mIgG and vis + mIgG groups. o, p, Violin plots showing the expression levels of Abcg2, Lrp1, Picalm, Rab5a, Rab7 and Rab11a in cBECs (o)and vBECs (p) from each group. Data in ap are from a single experiment in which the transcriptomes of 7,286 cells (isolated from brain hemispheres of 3 mice per group) were analysed, including 2,625 microglia, 1,958 cBECs, 545 aBECs and 1,412 vBECs; scale bar in e represents scaled expression at the single-cell level; differentially expressed genes plotted in h, k and m were determined using an F-test with adjusted degrees of freedom based on weights calculated per gene with a zero-inflation model and Benjamini–Hochberg adjusted P values; Gene Ontology analyses used over-representation test and scale bars in g, i, j, l and n represent Benjamini–Hochberg adjusted P values for each pathway; gene expression comparison in f, o and p was done using Wilcoxon rank-sum test with Bonferroni’s adjusted P values reported.

Extended Data Fig. 7 Improved brain Aβ plaque clearance by delivery of mVEGF-C and mAb158 into the CSF is correlated with lymphatic vessel expansion at the dorsal meninges and transcriptional reprogramming of meningeal LECs.

a, Adult 4- to 5-month-old male 5xFAD mice were injected with 5 μl (i.c.m.) of AAV1 expressing eGFP or mouse VEGF-C (mVEGF-C), under the cytomegalovirus (CMV) promoter (each at 1012 GC μl−1), in combination with either mAb158 antibodies or the respective mIgG control antibodies (each at 1 μg μl−1). Antibody injections (5 μl at 1 μg μl−1, i.c.m.) were repeated two weeks later. The same regimen of the aforementioned i.c.m. injections was repeated as indicated in the scheme and tissue was collected two weeks after the last injection. b, Representative images of brain sections stained for Aβ (red, stained with the D54D2 antibody) and with DAPI (blue; scale bar, 2 mm). c, Coverage of Aβ as percentage of brain section in each group. d, Representative images from the brain cortex stained for Aβ (blue, stained with the Amylo-Glo), CD68 (green) and IBA1 (red; scale bar, 50 μm). eg, Coverage by IBA1+ cells (e; percentage of field), number of peri-Aβ plaque IBA1+ cells (f) and percentage of IBA1 occupied by CD68 in each group (g). Results in c and eg are presented as mean ± s.e.m.; n = 12 in mVEGF-C + mIgG and n = 13 in eGFP + mIgG, eGFP + mAb158 and mVEGF-C + mAb158; two-way ANOVA with Holm–Sidak’s multiple comparisons test; data in ag are from two independent experiments. h, Representative fluorescence stereomicroscopy images of skull caps (skull bone signal in blue) and attached meningeal lymphatic vessels stained for LYVE-1 (green) around the transverse sinus (TS) at the dorsal meninges or around the sigmoid (SS) and petrosquamosal (PSS) sinuses at the basal meninges (scale bars, 500 μm). i, j, Total length of LYVE-1+ vessels (mm) and number of branching points in lymphatics at the dorsal (i) and basal (j) meninges. Results in hj are presented as mean ± s.e.m.; n = 6 in mIgG groups and n = 7 in mAb158 groups; two-way ANOVA with Holm–Sidak’s multiple comparisons test; data in hj are representative of two independent experiments. k, Representative images of meningeal whole mounts stained for CD31 (green) and LYVE-1 (red; scale bar, 1 mm; inset scale bar, 300 μm). l, m, Coverage by CD31+LYVE-1 vessels (l; % of meningeal whole mount) and the number of branching points and coverage by LYVE-1+ vessels (m; % of meningeal whole mount). Results in l and m are presented as mean ± s.e.m.; n = 7 in eGFP + mIgG and n = 6 in eGFP + mAb158, mVEGF-C + mIgG and mVEGF-C + mAb158; two-way ANOVA with Holm–Sidak’s multiple comparisons test; data in km are representative of two independent experiments. n, Aged wild-type mice (20–24 months of age) were injected with 2 μl (i.c.m.) of AAV1 expressing eGFP or mVEGF-C, under the CMV promoter (each at 1013 GC μl−1). One month later, mice were transcardially perfused, skull caps were collected, meninges harvested and LECs were sorted by FACS for bulk RNA-seq. o, PCA plot showing segregation between eGFP (orange) and mVEGF-C (blue) meningeal LEC transcriptomes. p, Volcano plot showing genes that were significantly downregulated (blue) or upregulated (orange) between meningeal LECs from the mVEGF-C and eGFP groups. q, Ten Gene Ontology terms (selected from the 30 most altered) obtained after analysis of genes that were differentially expressed between meningeal LECs from the mVEGF-C and eGFP groups. nq, n = 2 per group; individual RNA samples result from LECs pooled from ten meninges over two independent experiments; differentially expressed genes (P < 0.05) plotted in c were determined using an F-test with adjusted degrees of freedom based on weights calculated per gene with a zero-inflation model; Gene Ontology analysis in q used over-representation test and the scale bar represents the P value for each pathway. r, Aged APPswe mice (22–26 months of age) were treated with viral vectors expressing eGFP or mVEGF-C (via i.c.m. injections) and with mIgG or mAdu. antibodies (via i.p. injections, according to the regimen in the scheme; related to Fig. 2). s, Representative images of brain sections stained for Aβ (red, stained with the D54D2 antibody) and with DAPI (blue; scale bar, 1 mm). t, Graph showing coverage of Aβ (as percentage of the brain sections) in each group. Results in t are presented as mean ± s.e.m.; n = 6 per group; two-way ANOVA with Holm–Sidak’s multiple comparisons test; data in rt are from a single experiment. Source data

Extended Data Fig. 8 Therapeutic effects of mVEGF-C on the clearance of Aβ by antibodies in old APPswe mice and the gene expression profile of brain cells.

a, Aged APPswe mice (26–30 months old) were injected with 5 μl (i.c.m.) of AAV1 expressing eGFP or mVEGF-C (each at 1012 GC μl−1) in combination with mAb158 (at 1 μg μl−1) as indicated in the scheme. b, Representative images of brain sections from APPswe mice stained for Aβ (red, stained with the D54D2 antibody) and with DAPI (blue; scale bar, 1 mm). ce, Coverage of Aβ (percentage of brain region) in the hippocampus (c), cortex/striatum/amygdala (d) and combined regions (e). Results in ce are presented as mean ± s.e.m.; n = 11 per group; two-tailed unpaired Student’s t-test; data in ae are from a single experiment. f, Aged J20 mice (14–16 months old) were injected with 5 μl (i.c.m.) of AAV1 expressing eGFP or mVEGF-C (each at 1012 GC μl−1) in combination with mAb158 (at 1 μg μl−1) as indicated in the scheme. g, Representative images of brain sections from J20 mice stained for Aβ (red, stained with the D54D2 antibody) and with DAPI (blue; scale bar, 1 mm). hj, Coverage of Aβ (% of brain region) in the hippocampus (h), cortex/striatum/amygdala (i) and combined regions (j). Results in hj are presented as mean ± s.e.m.; n = 8 in eGFP + mAb158 and n = 10 in mVEGF-C + mAb158; two-tailed unpaired Student’s t-test; data in fj are from a single experiment. k, Top ten Gene Ontology terms obtained after analysing genes that were significantly upregulated in hippocampi (n = 3 per group) from the eGFP + mAdu group when compared to the eGFP + mIgG group (related to Fig. 2a–c). l, m, Heat maps depicting the expression profile of genes in the learning and memory (l; GO: 0007611) and synapse organization (m; GO: 0050808) Gene Ontology pathways (related to Fig. 2d, e). Data in km are from a single experiment; Gene Ontology analyses used over-representation test and scale bar in k represents Benjamini–Hochberg adjusted P values; heat maps in l and m depict counts-per-million normalized expression minus per-gene mean expression. n, Representation of the tSNE plot highlighting sequenced brain cells by group. o, Dot plot depicting the average scaled expression levels of specific genes (x-axis) used to identify the brain cell populations, as well as the percentage of gene-expressing cells within each population; smooth muscle cells (SMCs) choroid plexus blood endothelial cells (cpBECs), border-associated macrophages (BAMs), venous BECs (vBECs), arterial BECs (aBECs) and capillary BECs (cBECs). ps, Volcano plots, with significantly downregulated (in blue) and upregulated (in orange) genes, and Gene Ontology terms (obtained using upregulated genes; selected from top 20 terms) obtained after comparing the transcriptomes of vBECs (p, q) and aBECs (r, s) from the mVEGF-C + mIgG group and the eGFP + mIgG group. t, Violin plots showing the expression levels of the Flt4 gene in microglia, capillary, venous and arterial BECs in each group. Data in nt are related to Fig. 2f–k and resulted from a single experiment in which the transcriptomes of 7,739 cells (isolated from brain hemispheres of 3 mice per group) were analysed, including 2,345 microglia, 2,934 cBECs, 602 vBECs and 766 aBECs; differentially expressed genes plotted in p and r were determined using an F-test with adjusted degrees of freedom based on weights calculated per gene with a zero-inflation model and Benjamini–Hochberg adjusted P values; Gene Ontology analyses used over-representation test and scale bars in q and s represent Benjamini–Hochberg adjusted P values for each pathway; gene expression comparison in t was done using Wilcoxon rank-sum test with Bonferroni’s P value adjustment. Source data

Extended Data Fig. 9 Expression profile of genes associated with Parkinson’s disease, multiple sclerosis and AD in meningeal LECs, brain blood endothelial cells and microglia from different mouse models.

a, Pie chart showing the proportion of Parkinson’s disease-associated genes for which the average expression across all RNA-seq datasets of lymphatic endothelial cells (LECs) was in the top 2nd, 5th, 10th, or 25th percentile out of all genes. b, Heat map showing the log2-normalized expression values (depicted in the colour scale bar) for Parkinson’s disease-associated genes whose average expression values fall within the top second percentile of all genes expressed across all LEC RNA-seq datasets. c, Gene-sets obtained by functional enrichment of 25th percentile Parkinson’s disease-associated genes expressed across all LEC RNA-seq datasets. d, Pie chart showing the proportion of multiple sclerosis-associated genes for which the average expression across all LEC RNA-seq datasets was in the top 2nd, 5th, 10th, or 25th percentile out of all genes. e, Heat map showing the log2-normalized expression values (depicted in the colour scale bar) for multiple sclerosis-associated genes whose average expression values fall within the top second percentile of all genes expressed across all LEC RNA-seq datasets. f, Gene-sets obtained by functional enrichment of 25th percentile multiple sclerosis-associated genes expressed across all LEC RNA-seq datasets. g, Pie chart showing the proportion of AD-associated genes for which the average expression across all LEC RNA-seq datasets was in the top 2nd, 5th, 10th, or 25th percentile out of all genes. h, Heat map showing the log2-normalized expression values (depicted in the colour scale bar) for AD-associated genes whose average expression values fall within the top second percentile of all genes expressed across all LEC RNA-seq datasets. i, Gene-sets obtained by functional enrichment of 25th percentile AD-associated genes expressed across the different LEC RNA-seq datasets. ai, n = 2 or 3 per group; individual RNA samples result from LECs pooled from 10 mice; genes used in ai are from RNA-seq datasets obtained from LECs isolated from diaphragm, ear skin and meninges at 2–3 months (m.), from meninges at 2–3 or 20–24 months, from meninges at 20–24 months after injections with AAV1-CMV-eGFP (eGFP) or AAV1-CMV-mVEGF-C-WPRE (mVEGF-C, one month after i.c.m. injection; see Methods for details) and from meninges of 6-month-old wild-type or 5xFAD mice (see Extended Data Fig. 1f-k for related data); in c, f and i the Benjamini–Hochberg correction was used to adjust the associated P values (Padj < 0.05) and the functional enrichment of differential expressed genes was determined with Fisher’s exact test. j, Pie charts showing the proportion of AD-associated genes for which the average expression was in the top 2nd, 5th, 10th, or 25th percentile out of all genes in each cluster of brain blood endothelial cells (BECs): capillary BECs 1, capillary BECs 2, arterial BECs and venous BECs. k, Heat map showing the expression values for AD-associated genes whose average expression values fall within the top second percentile of all genes expressed in each cluster of BECs. l, The transcriptome of myeloid cells (live CD45+Ly6GCD11b+ cells) sorted from the brain cortex of 5.5-month-old 5xFAD mice was analysed by scRNA-seq (Methods). The graph shows the unsupervised clustering and tSNE representation of four distinct clusters of microglia (Mg). m, Pie charts showing the proportion of AD-associated genes for which the average expression was in the top 2nd, 5th, 10th, or 25th percentile out of all genes in each Mg cluster. n, Heat map showing the expression values for AD-associated genes whose average expression values fall within the top second percentile of all genes expressed in each Mg cluster. o, Venn diagram showing the overlap between AD-associated genes in the top tenth percentile for meningeal LECs (mLECs), brain BECs (bBECs) and microglia. Data in j and k resulted from the analysis of a published scRNA-seq dataset25; data in ln resulted from the scRNA-seq analysis of 651 microglia; in k and n, scale bars represent log2-normalized expression values. Source data

Extended Data Fig. 10 Integrative analyses of gene expression profiles of microglia from the brains of 5xFAD mice with intact or ablated meningeal lymphatics and from the human brain.

a, Representation of the tSNE plots showing the segregation of microglia from human donors or 5xFAD mice by groups (dashed lines represent the approximate boundaries between microglial clusters) upon cross-species RNA-seq data integration and analysis (Fig. 3b). b, c, Violin plots showing expression levels of the pan-microglial genes ELMO1, MALAT1 and MEF2A and the homeostatic genes P2RY12, P2RY13 and TMEM119 (b) and the activation genes CD83, CST3, JUN, LGMN, LPL and TNFAIP3 (c) in the different human microglial clusters. d, Dot plot depicting the average scaled expression levels of specific genes (x-axis), as well as the percentage of gene-expressing 5xFAD microglia within each cluster. Data in ad are related to Fig. 3b-g and were obtained from the integrated analysis of a total of 5,462 non-AD, 618 presymptomatic AD, 4,548 familial AD and 6,461 sporadic AD microglia (single-nucleus RNA-seq data) from human brain parietal lobes, and from a total of 781 and 770 microglia (scRNA-seq data) from the brains of 5xFAD mice of the vis + mIgG and vis/photo + mIgG groups, respectively.

Supplementary information

Supplementary Information

Full names and credentials of the Dominantly Inherited Alzheimer Network (DIAN) Consortium members.

Reporting Summary

Supplementary Table 1

List of DEGs in brain cell types of the Vis./photo. plus mIgG group compared to the Vis. plus mIgG group. Depicts the number of differentially expressed genes, alongside the respective Log2(fold change) and adjusted P-values, in microglia, capillary blood endothelial cells, venous blood endothelial cells and arterial blood endothelial cells from the Visudyne/photoconversion plus mIgG group, compared to the control Visudyne plus mIgG group.

Supplementary Table 2

Comparisons between the expression levels of homeostatic and DAM genes in mouse microglia from different groups. This table depicts the Log2(fold change) and adjusted P-values for the differential expression levels of homeostatic, Trem2 independent and Trem2 dependent microglial genes (associated with the acquisition of the disease-associated microglia signature) in Visudyne plus mAducanumab vs Visudyne plus mIgG, in Visudyne/photoconversion plus mIgG vs Visudyne plus mIgG, in Visudyne/photoconversion plus mAducanumab vs Visudyne/photoconversion plus mIgG and in Visudyne/photoconversion plus mAducanumab vs Visudyne plus mAducanumab.

Supplementary Table 3

Gene-set based analyses for highly expressed AD-related gene SNPs in meningeal lymphatic endothelial cells, brain blood endothelial cells or microglia. This table depicting the gene-set analyses was performed using the Generalized Gene-Set Analysis of GWAS Data (MAGMA) analyses, which maps every SNP to the nearest gene, takes into account LD structure and uses multiple regression analyses to provide a P-value for the association of each gene with the tested phenotype, namely amyloid imaging, sTREM2, Aβ42, pTau, Tau, age at onset, disease risk and disease progression.

Supplementary Table 4

Demographic characteristics of donor brain samples used in single-nucleus RNA-seq experiments. This table depicts the number of samples, brain regions, sex, age of death, proportions of APOE ε4 carriers and post-mortem interval for the non-AD, presymptomatic AD, familial AD and sporadic AD patient groups.

Supplementary Table 5

Microglial gene signature of meningeal lymphatic dysfunction in 5xFAD. Table depicting the 54 genes, and corresponding Log2(fold change) and q-values, that compose the signature of microglial activation in 5xFAD mice with ablated meningeal lymphatics (Visudyne/photoconversion plus mIgG group) compared to 5xFAD mice with intact meningeal lymphatics (Visudyne plus mIgG group).

Supplementary Table 6

Gene-set based analyses for genes overexpressed in microglia upon meningeal lymphatic ablation in 5xFAD or treatment with mVEGF-C in APPswe. Table depicting the gene-set analyses performed using the Generalized Gene-Set Analysis of GWAS Data (MAGMA) analyses, which maps every SNP to the nearest gene, takes into account LD structure and uses multiple regression analyses to provide a P-value for the association of each gene with the tested phenotype, namely amyloid imaging, sTREM2, Aβ42, pTau, Tau, age at onset and disease risk.

Source Data

This file contains Source Data for Supplementary Table 3.

Source Data

This file contains Source Data for Supplementary Table 6.

Video 1

Drainage of fluorescent microspheres injected into the CSF of mice with intact meningeal lymphatics. Yellow-green fluorescent (505/515 nm) microspheres (0.5 µm in diameter) were injected into the CSF of adult mice with intact meningeal lymphatic vasculature. The video shows microspheres flowing through lymphatic vessels afferent to the deep cervical lymph node for a total of 20 seconds. Tracking of microspheres was highlighted using TrackMate.

Video 2

Drainage of fluorescent microspheres injected into the CSF of mice with ablated meningeal lymphatics. Yellow-green fluorescent (505/515 nm) microspheres (0.5 µm in diameter) were injected into the CSF of adult mice that undergone meningeal lymphatic vessel ablation. The video shows microspheres flowing through lymphatic vessels afferent to the deep cervical lymph node for a total of 20 seconds. Tracking of microspheres was highlighted using TrackMate.

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Da Mesquita, S., Papadopoulos, Z., Dykstra, T. et al. Meningeal lymphatics affect microglia responses and anti-Aβ immunotherapy. Nature 593, 255–260 (2021). https://doi.org/10.1038/s41586-021-03489-0

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