HUMAN GENOMICS

Spatiotemporal dynamics ofmolecular pathology in amyotrophiclateral sclerosisSilas Maniatis1*, Tarmo Äijö2*, Sanja Vickovic1,3,4*, Catherine Braine1,5, Kristy Kang1,Annelie Mollbrink4, Delphine Fagegaltier1, Žaneta Andrusivová4, Sami Saarenpää4,Gonzalo Saiz-Castro4, Miguel Cuevas5, Aaron Watters2, Joakim Lundeberg4,6†,Richard Bonneau2,7†, Hemali Phatnani1,5†

Paralysis occurring in amyotrophic lateral sclerosis (ALS) results from denervationof skeletal muscle as a consequence of motor neuron degeneration. Interactionsbetween motor neurons and glia contribute to motor neuron loss, but thespatiotemporal ordering of molecular events that drive these processes in intactspinal tissue remains poorly understood. Here, we use spatial transcriptomicsto obtain gene expression measurements of mouse spinal cords over the courseof disease, as well as of postmortem tissue from ALS patients, to characterizethe underlying molecular mechanisms in ALS. We identify pathway dynamics,distinguish regional differences between microglia and astrocyte populations atearly time points, and discern perturbations in several transcriptional pathwaysshared between murine models of ALS and human postmortem spinal cords.

Amyotrophic lateral sclerosis (ALS) is aprogressive neurodegenerative disease inwhich symptoms often manifest at firstin distal muscles of a single limb. Symp-toms then spread throughout the body,

ultimately leading to total paralysis. However,the events that initiate disease pathology, andthe mechanisms through which it becomes per-vasive, remain poorly understood (1). Mountingevidence indicates that dysfunction in signalingbetween motor neurons and glia is a key com-ponent of the disease (1–3). Inherent limitationsof current gene expression profiling technolo-gies, such as low throughput or lack of spatialresolution, have thus far frustrated efforts tounderstand how such dysfunction participatesin the onset and spread of ALS pathology in thespinal cord. Given the stereotyped cellular orga-nization of the spinal cord and importance ofintercellular communication in ALS progres-sion, we reasoned that a spatially resolved viewof disease-driven gene expression changes wouldbe needed to order these events, reveal the re-levant subpopulations of cells involved in eachstage in disease progression, and characterize

the underlying molecular mechanisms that trig-ger and maintain the disease phenotype.Spatial transcriptomics (ST) generates quanti-

tative transcriptome-wide RNA sequencing (RNA-seq) data through capture of polyadenylatedRNA on arrays of spatially barcoded DNA captureprobes (4). The workflow does not require spe-cialized equipment, does not require preselectionof genes to interrogate, and has a throughputsubstantially greater than that of other spatiallyresolved methods. We applied ST to spatially pro-file gene expression in lumbar spinal cord tissuesections (L3 to L5) from SOD1-G93A (ALS) andSOD1-WT (control) mice at presymptomatic,onset, symptomatic, and end-stage time points(table S1). We then applied ST to profile geneexpression in postmortem lumbar and cervicalspinal cord tissue sections from either lumbar-or bulbar-onset sporadic ALS patients, resulting inmore than 76,000 spatial gene expression mea-surements (SGEMs)mapping to ~1200 spinal cordtissue sections of 67 mice, and more than 60,000SGEMs mapping to 80 postmortem spinal cordtissue sections from seven patients (table S1).All raw data have been deposited publicly, as de-scribed below. Additionally, an interactive dataexploration portal is publicly available at https://als-st.nygenome.org/.We annotated each SGEMwith an anatomical

annotation region (AAR) tag and used these tagsto conduct differential expression analysis and toregister the data to a common coordinate system(figs. S1 and S2 and table S1). To estimate geneexpression levels accurately and detect signifi-cant regional, anatomical, and cell type changeswithin and between conditions, we formulated ahierarchical generative probabilistic model (sup-plementary methods). Our model corrects formissing data due to undersampling and bias, an

issue in spatial and single-cell RNA-seq (scRNA-seq) studies. We thus reliably quantitated thespatial distribution of 11,138 genes in mouseand 9624 genes in human spinal cord sections.Furthermore, principal component analysis ofthe complete mouse SGEM dataset reveals thatmost of the variance is explained by spatial lo-cation, disease state, and genotype (fig. S3), andnot by batch effects.Our analysis reveals altered expression of sev-

eral known ALS genes (e.g., Matr3, Kif5a, andPfn1) (https://als-st.nygenome.org) (5). Our anal-ysis also recapitulates the specific regional andtemporal expression patterns for genes withdescribed regional expression profiles (6–8) androles in ALS progression. Immunofluorescence(IF) imaging of the protein products of thesegenes demonstrates spatial concordance withour analysis (Fig. 1 and tables S2 and S3). Fur-thermore, our data suggest that microglial dys-function occurs well before symptom onset,precedes astroglial dysfunction in ALS, and isproximal to motor neurons (table S3 and fig. S4).To further explore the spatiotemporal dynam-

ics of microglial activation, we focused on amechanism involving TREM2 reported in neuro-degenerative disease models (3, 9). TREM2 andTYROBP form a receptor complex that can trig-ger phagocytosis or modulate cytokine signalingwhen engaged bymembrane lipids, or lipoproteincomplexes (9, 10). This mechanism also involvesApoe, Lpl, B2m, and Cx3cr1 and is activated bymicroglial phagocytosis of apoptotic neurons.Spatial gene expression analysis suggests a spa-tiotemporal ordering of this TREM2-mediatedmechanism in this mouse model of ALS. We ob-serve that Tyrobp expression is up-regulated pre-symptomatically and before Trem2 in the ventralhorn and ventral white matter. Furthermore, Lpland B2m are simultaneously up-regulated (pre-symptomatically) specifically in the ventral horn,whereasApoe and Cx3cr1 are not (Fig. 2, table S3,and fig. S4). Expression of these latter genes be-comes widely up-regulated in spinal cords ofsymptomatic mice (table S3). Apoe expression isdriven by Trem2 signaling and is itself a ligandfor Trem2. Therefore, Apoe and Trem2 act in anautoregulatory loop that can trigger and main-tain a phagocytic microglial phenotype (3). Col-lectively, our analysis suggests that TREM2- andTYROBP-mediated signaling is an early step indisease-relevant changes in microglial gene ex-pression and reveals the spatiotemporal orderingof these changes.Trem2 mutations are associated with several

neurodegenerative diseases (10–12) and, throughmammalian target of rapamycin (mTOR) sig-naling in myeloid cells (10), Trem2 expressionmodulates autophagy. Mutations in severalautophagy-related genes are associated withALS (10). ST analysis and IF imaging showthat genes involved in autophagy and the endo-lysosomal system are dysregulated in the spinalcord of this ALS mouse model (fig. S5 and tableS3). Ablation of autophagy by conditional knock-out of Atg7 in cholinergic cells, including motorneurons (ChAT-Cre+/+; Atg7 fl/fl; SOD1-G93A),

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1Center for Genomics of Neurodegenerative Disease, NewYork Genome Center, New York, NY, USA. 2Center forComputational Biology, Flatiron Institute, New York, NY, USA.3Broad Institute of MIT and Harvard, Cambridge, MA, USA.4Science for Life Laboratory, Department of GeneTechnology, KTH Royal Institute of Technology, Stockholm,Sweden. 5Mortimer B. Zuckerman Mind Brain BehaviorInstitute, Columbia University, New York, NY, USA.6Department of Bioengineering, Stanford University,Stanford, CA, USA. 7Center for Data Science, New YorkUniversity, New York, NY, USA.*These authors contributed equally to this work.†Corresponding author. Email: hphatnani@nygenome.org (H.P.);rb133@nyu.edu (R.B.); joakim.lundeberg@scilifelab.se (J.L.)

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Z maximum projection of 10-mm confocal immunofluorescence imagestack (N = 7 animals) (bottom right). Scale bar, 500 mm. (B) Spatial mRNAexpression of Aif1 and Gfap at postnatal day 70 (P70) and P100.(C) Z maximum projections of 10-mm confocal immunofluorescence imagestacks at P70 and P100 (N = 12 animals). Scale bars, 250 mm.

Fig. 2. Presymptomaticdysregulation ofTREM2- and TYROBP-mediated signaling.(A) The posterior distri-butions of coefficientparameters b of Tyrobp atP30, P70, P100, andP120. The coefficientparameters b captureoffsets of expression(in natural logarithmicspace) in distinct AARsacross all tissue sectionsof a given condition.(B) As in (A), for Trem2.(C) Spatial mRNAexpression of Tyrobpat P70. (D) Z maximumprojections of 10-mmconfocal immuno-fluorescence imagestacks in ventral-lateralspinal cords at P70(N = 6 animals). Scalebar, 250 mm.

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leads to earlier symptom onset but prolongedsurvival in ALS mice (2). This manipulation alsopartially rescues reactive gliosis in ALS mice. Toinvestigate which pathways might link dysfunc-tion in autophagy to gliosis and motor neuronloss in ALS, we applied ourmethods to thesemice(Atg7 cKO). As expected, we observe that ex-pression of Gfap and Aif1, and activity of theTREM2 microglial activation axis, are greatly re-duced when autophagy is ablated in motor neu-rons, particularly in AARs distal tomotor neuronsomata (table S3).To better understand disease-relevant changes

in gene regulation and interactions betweencell types, we carried out an unbiased coex-pression analysis of our mouse ST data. Weidentified 31 major coexpression modules (13)(Fig. 3A and table S4) of diverse spatiotemporaland pathway activities, a subset of which is af-fected in Atg7 cKO (Fig. 3B, figs. S6 and S7A, andtable S5). In the context of published scRNA-seqdata (14), many of the modules are composed ofgenes preferentially expressed in specific celltypes (fig. S7B). We grouped the genes of eachmodule on the basis of their cell type–specificexpression pattern, resulting in submodules (13)(Fig. 3C and tables S6 and S7). Submodules thatare enriched for a given cell type can display dis-tinct spatiotemporal expression patterns depend-

ing on the parent module from which they arederived. Such differences represent functionallydistinct subpopulations within that cell type. Forexample, submodules containing Prdx6 and Gfap(submodule 8.9) or Slc7a10 and Bcan (submod-ule 29.41) represent regional astrocyte subpopu-lations that behave differently across the courseof disease (fig. S8A). In ALS animals, the Prdx6submodule displays increasing activity as diseaseprogresses, whereas the Slc7a10 submodule isattenuated with progression. Intriguingly, thedisease-related dynamics of the Prdx6 astrocytesubmodule in ALS animals are rescued in Atg7cKO, but those of the Slc7a10 astrocyte submoduleare not. Our spatial analysis thus identifies geneexpression programs characteristic of regionalastrocyte populations (15) that display distinct,disease-relevant spatiotemporal dynamics and aredifferentially dependent on cholinergic autophagy.This approach also allows us to identify co-

ordinated activities across cell types that reflectmajor aspects of disease and to highlight expres-sion programs within distinct cell types associ-ated with these processes (fig. S7B). In one suchexample, a microglial expression program con-taining Trem2, Tyrobp, Aif1, and other reactivemicroglial genes displays spatiotemporal dynam-ics reflecting patterns of progressive gliosis inALS (submodule 8.17) (3, 16, 17). A second mi-

croglial expression program containing Lrp1 andGba (submodule 8.4) exhibits spatiotemporal dy-namics correlated with those of the Trem2 mi-croglial submodule 8.17. Kyoto Encyclopedia ofGenes andGenomes (KEGG) pathway enrichmentanalysis of these submodules shows that theyare both enriched for lysosomal factors (Fig. 3D).However, whereas the Trem2 submodule includesmany factors involved in the complement cascade,Fc receptor–mediated signaling, and phagocyto-sis, the Lrp1 submodule includes many sphin-golipid signaling factors. Both the Trem2 andLrp1 submodules exhibit correlated spatiotem-poral dynamics with astrocyte submodule 8.9.Lastly, the activity of thesemicroglial and astroglialsubmodules is correlated with activities of oligo-dendrocyte precursor (OPC) submodule 8.24 andmature oligodendrocyte submodules 8.18 and8.19 (fig. S8B). Notably, the spatiotemporal patternofmodule 8 expression is rescued by ablation ofautophagy in cholinergic neurons in Atg7 cKOmice, demonstrating the key role that neuralinteractions with module 8 glia play in theseactivities. Collectively, the pathway activitiesencompassed by module 8 reveal signalingwithin and between cell types during early glialactivation in intact tissue and the mechanismsthat maintain and spread the reactive phenotypein the ALS mouse model.

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Pathways in cancerHTLV-I infection

Leukocyte transendothelial migrationPI3K-Akt signaling pathway

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ECM-receptor interactionSmall cell lung cancer

Cytokine-cytokine receptor interactionHepatitis B

Regulation of actin cytoskeletonRap1 signaling pathway

AmoebiasisProtein digestion and absorption

PeroxisomeOsteoclast differentiation

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Glycosaminoglycan degradationChagas disease (American trypanosomiasis)

Fc gamma R-mediated phagocytosisLeishmaniasis

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Fig. 3. Spatiotemporal dynamics of gene expression during diseaseprogression in ALS. (A) Biclustering of the mouse SGEMs revealsspatially and temporally coexpressed genes. The dashed vertical purpleline in the dendrogram denotes the break. Identifiers of coexpressionmodules are listed. (B) Average spatiotemporal expression dynamics ofmodules 8 and 11. (C) Hierarchical clustering of genes in module 8 using

independent gene expression data of mouse central nervous system celltypes. The dashed purple line in the dendrogram denotes the break.Identifiers for submodules having at least 10 genes are listed. Selectedgenes are noted. (D) Analysis of enriched KEGG pathways amongthe genes for submodules in (C) [one-tailed Fisher’s exact test withBenjamini-Hochberg correction; FDR (false discovery rate) < 0.1].

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A microglial expression program that includesSall1 (submodule 1.12) is increased in the whitematter of control and presymptomatic ALS ani-mals (fig. S8C). Sall1 is expressed by homeostaticmicroglia, and loss of Sall1 expression in microg-lia results in a phagocytic, inflammatory pheno-type (3). The expression pattern of the Sall1submodule illustrates glial interactions that arespatiotemporally and mechanistically distinctfrom those of module 8. By the end stage in ALSanimals, this submodule has infiltrated the graymatter and is attenuated in the white matter.This expression program is coordinated withastrocyte submodule 1.15 and oligodendrocytesubmodule 1.8 (fig. S8D). Expression of Sall1 inthis submodule suggests that the late-stage ex-pansion of the microglial population responsiblefor this expression program differs from the re-active microglial populations present in modules 8and 6 (fig. S8C). Further, the collective spatio-temporal expression pattern of module 1 in ALSanimals is consistent with late-stage defects inmyelination (6). Notably, Atg7 cKO does not res-cue the dynamics of this expression module,which encompasses the activities of multiplecell types. Thus, spatiotemporal correlation ofthe microglial, astroglial, and the oligodendro-cyte expression programs in module 1 suggeststhe coordination of signaling mechanisms inglial behavior related to axonal pathology in late-stage ALS animals. Taken together, these exam-ples demonstrate how disease-related processesare exemplified with the combination of scRNA-seq and ST.We applied our ST workflow to cervical and

lumbar tissue from four human ALS patientswho presented clinically with bulbar symptomonset and three patients who presented withlower limb symptom onset. These individualsexhibit expected regional expression patterns,resembling those from the mouse dataset (fig.S9). Consistent with previous studies (18, 19),our observations appear to support the notionthat the severity of ALS pathology is related toproximity to site of symptom onset—human spa-tial data show variability in gene expression inthe anterior horn related to such proximity (tableS10). For instance, the gene encoding acetylcho-linesterase (ACHE), the activity of which hasbeen linked to neuromuscular defects in ALS(20), shows reduced expression at locations pro-ximal to spinal segments innervating the site ofsymptom onset (Fig. 4, A and B). As with themouse spatial data, we conducted an unbiasedcoexpression analysis on the human spatial data,resulting in 28 human expression modules ofwhich some are preserved between mouse andhuman (figs. S10, A and B, and S11 and table S8).The spatial mapping patterns for these humanexpression modules demonstrate AAR charac-teristic patterns, some of which vary along therostrocaudal axis (Fig. 4C), or differ betweenwhite matter and gray matter (fig. S10B), orwith proximity to site of symptom onset (fig.S10B). For example, consistent with previousstudies (18), human expression module 1, whichincludes genes involved in VEGF and glutama-

tergic signaling, is attenuated in lumbar sec-tions from patients that have a lower limb siteof onset (fig. S10B). In addition, human expres-sion module 3 is attenuated across spinal cordsections at sites proximal to symptom onset(Fig. 4C). Furthermore, this attenuation is mostpronounced in the posterior white matter andanterior horns. KEGG analysis shows that humanmodule 3 is enriched for several pathways, in-cluding sphingolipid, retrograde endocannabinoid,and WNT signaling (fig. S10C and table S9). Thisfinding, alongwith humanandmouse submodulesthat display disease-relevant dynamics and areenriched for sphingolipid signaling pathways,underscores the importance of this mechanism inALS pathology. Indeed, altered glycosphingolipidlevels and their metabolism have been reportedin spinal cords of ALS patients and in murinemodels of SOD1 ALS (21). Modulators of sphingo-lipid signaling have been proposed as potentialtherapeutics for ALS and improve the disease inmurine models of ALS (21, 22). Our data detailthe dynamics of sphingolipid signaling in multi-ple cell types, spinal cord regions, and diseasestages and suggest target opportunities for de-signing therapeutics. Further, the spatiotemporalnature of our data provides insight for potentialtreatment strategies modulating the activity ofthis pathway.Taken together, we provide a comprehensive

spatiotemporal, transcriptome-wide gene expres-

sion dataset combining resolution, replication,and biological perturbation. Our procedure allowsus to draw inferences from murine models andtest them in clinical samples. As such, we expectthe work presented here to be a resource to spurfurther mapping of the central nervous systemand its modes of dysfunction.

REFERENCES AND NOTES

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(2019).11. S. A. Liddelow et al., Nature 541, 481–487 (2017).12. M. Boutry et al., Cell Reports 23, 3813–3826 (2018).13. Materials and methods are available as supplementary materials.14. A. B. Rosenberg et al., Science 360, 176–182 (2018).15. A. V. Molofsky et al., Nature 509, 189–194 (2014).16. S. Vinsant et al., Brain Behav. 3, 335–350 (2013).17. S. Vinsant et al., Brain Behav. 3, 431–457 (2013).18. A. R. Jones et al., Neurobiol. Aging 36, 2006.e1–2006.e9

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Fig. 4. Spatiotemporal transcriptome of human postmortem spinal cord tissue from ALSpatients. (A) The posterior difference distributions of the ventral horn coefficients for ACHE perpatient (D1 to D4). Differences are calculated between distal and proximal regions with respect to theonset location. (B) Spatial mRNA expression of ACHE in human postmortem lumbar and cervicalspinal cord. (C) Average spatiotemporal expression dynamics for human coexpression modules 3,25, and 27 are visualized.

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ZENODO.2566612.

ACKNOWLEDGMENTS

We thank Target ALS Multicenter Postmortem Core for providinghuman postmortem tissue; G. Akbalik, J. Gregory, I. Hubbard,D. Kim, and K. Wei for manual anatomical annotation; T. Maniatisfor Atg7 cKO mice; the Flatiron Institute for computationalresources; and NGI Stockholm and SciLifeLab for infrastructuresupport. Funding: The study was supported by Target ALS,The ALS Association (grant no. 15-LGCA-234), The Tow Foundation,

the Knut and Alice Wallenberg Foundation, and the SimonsFoundation. Author contributions: H.P., S.M., and S.V. designedthe experiments. S.M. and S.V. performed the experiments, withhelp from C.B., K.K., M.C., Ž.A., S.S, G.S.-C., and A.M. T.Ä. andR.B. developed and implemented the Bayesian generative modeland the interactive data exploration portal. S.M., T.Ä., S.V., and D.F.analyzed the data. A.W. implemented the SGEM annotation tool.All authors discussed the results and wrote the manuscript.Competing interests: J.L. is an author on a patent applied for bySpatial Transcriptomics AB/10x Genomics Inc. covering thedescribed technology. Data and materials availability: Raw andprocessed mouse data and images have been deposited at NCBI’sGene Expression Omnibus (GEO) Repository under project IDGSE120374. Raw human data have been deposited at New York

Genome Center and are available upon request submitted toalsdata@nygenome.org. A code implementing the used statisticalmodel is available at (23). All processed data and images used inthe analyses have been deposited to https://als-st.nygenome.org/.

SUPPLEMENTARY MATERIALS

www.sciencemag.org/content/364/6435/89/suppl/DC1Materials and MethodsFigs. S1 to S16Tables S1 to S10References (24–43)

12 November 2018; accepted 1 March 201910.1126/science.aav9776

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Spatiotemporal dynamics of molecular pathology in amyotrophic lateral sclerosis

and Hemali PhatnaniAndrusivová, Sami Saarenpää, Gonzalo Saiz-Castro, Miguel Cuevas, Aaron Watters, Joakim Lundeberg, Richard Bonneau Silas Maniatis, Tarmo Äijö, Sanja Vickovic, Catherine Braine, Kristy Kang, Annelie Mollbrink, Delphine Fagegaltier, Zaneta

DOI: 10.1126/science.aav9776 (6435), 89-93.364Science 

, this issue p. 89ScienceALS.they identified disease-associated pathways and established the key steps in motor neuron degeneration observed inthe spinal cord of a mouse ALS model and a postmortem human ALS spinal cord. From changes in gene expression,

used RNA sequencing to define transcriptomic changes over the course of disease in different regions ofet al.Maniatis the spinal cord. It has proven difficult to identify the early stages of disease and where it spreads within the body.

Amyotrophic lateral sclerosis (ALS) is a progressive motor neuron disease that affects nerve cells in the brain andSpatiotemporal gene expression in ALS

ARTICLE TOOLS http://science.sciencemag.org/content/364/6435/89

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REFERENCES

http://science.sciencemag.org/content/364/6435/89#BIBLThis article cites 41 articles, 7 of which you can access for free

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