The astrocyte-produced growth factor HB-EGF limits autoimmune CNS pathology.
Journal
Nature immunology
ISSN: 1529-2916
Titre abrégé: Nat Immunol
Pays: United States
ID NLM: 100941354
Informations de publication
Date de publication:
26 Feb 2024
26 Feb 2024
Historique:
received:
09
03
2023
accepted:
12
01
2024
medline:
27
2
2024
pubmed:
27
2
2024
entrez:
26
2
2024
Statut:
aheadofprint
Résumé
Central nervous system (CNS)-resident cells such as microglia, oligodendrocytes and astrocytes are gaining increasing attention in respect to their contribution to CNS pathologies including multiple sclerosis (MS). Several studies have demonstrated the involvement of pro-inflammatory glial subsets in the pathogenesis and propagation of inflammatory events in MS and its animal models. However, it has only recently become clear that the underlying heterogeneity of astrocytes and microglia can not only drive inflammation, but also lead to its resolution through direct and indirect mechanisms. Failure of these tissue-protective mechanisms may potentiate disease and increase the risk of conversion to progressive stages of MS, for which currently available therapies are limited. Using proteomic analyses of cerebrospinal fluid specimens from patients with MS in combination with experimental studies, we here identify Heparin-binding EGF-like growth factor (HB-EGF) as a central mediator of tissue-protective and anti-inflammatory effects important for the recovery from acute inflammatory lesions in CNS autoimmunity. Hypoxic conditions drive the rapid upregulation of HB-EGF by astrocytes during early CNS inflammation, while pro-inflammatory conditions suppress trophic HB-EGF signaling through epigenetic modifications. Finally, we demonstrate both anti-inflammatory and tissue-protective effects of HB-EGF in a broad variety of cell types in vitro and use intranasal administration of HB-EGF in acute and post-acute stages of autoimmune neuroinflammation to attenuate disease in a preclinical mouse model of MS. Altogether, we identify astrocyte-derived HB-EGF and its epigenetic regulation as a modulator of autoimmune CNS inflammation and potential therapeutic target in MS.
Identifiants
pubmed: 38409259
doi: 10.1038/s41590-024-01756-6
pii: 10.1038/s41590-024-01756-6
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council)
ID : HICI 851693
Organisme : EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council)
ID : HICI 851693
Organisme : EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council)
ID : 818170
Organisme : EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council)
ID : 818170
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : 408885537
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : 270949263
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : RO4866/3-1
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : 270949263 - GRK2162
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : Project ID 270949263 - GRK2162, Project ID 405969122 - FOR2886
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : 3908571
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : RO4866/3-1, 408885537 - TRR 274
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : 408885537 - TRR 274
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : 505539112 - GB.com
Organisme : Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
ID : R01MH130458, R00NS114111
Organisme : Foundation for the National Institutes of Health (Foundation for the National Institutes of Health, Inc.)
ID : NS087867, ES025530, ES032323, AI126880 and AI149699
Organisme : Forskningsrådet om Hälsa, Arbetsliv och Välfärd (Swedish Research Council for Health, Working Life and Welfare)
ID : 2018-05973
Organisme : Forskningsrådet om Hälsa, Arbetsliv och Välfärd (Swedish Research Council for Health, Working Life and Welfare)
ID : 2021-02977
Informations de copyright
© 2024. The Author(s).
Références
Lassmann, H. Multiple sclerosis pathology. Cold Spring Harb. Perspect. Med. 8, a028936 (2018).
pubmed: 29358320
pmcid: 5830904
doi: 10.1101/cshperspect.a028936
Thompson, A. J. et al. Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. Lancet Neurol. 17, 162–173 (2018).
pubmed: 29275977
doi: 10.1016/S1474-4422(17)30470-2
Polman, C. H. et al. Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Ann. Neurol. 69, 292–302 (2011).
pubmed: 21387374
pmcid: 3084507
doi: 10.1002/ana.22366
Miller, D., Barkhof, F., Montalban, X., Thompson, A. & Filippi, M. Clinically isolated syndromes suggestive of multiple sclerosis, part I: natural history, pathogenesis, diagnosis, and prognosis. Lancet Neurol. 4, 281–288 (2005).
pubmed: 15847841
doi: 10.1016/S1474-4422(05)70071-5
Lebrun-Frénay, C. et al. Risk factors and time to clinical symptoms of multiple sclerosis among patients with radiologically isolated syndrome. JAMA Netw. Open 4, e2128271 (2021).
pubmed: 34633424
pmcid: 8506228
doi: 10.1001/jamanetworkopen.2021.28271
Brownlee, W. J. et al. Early imaging predictors of long-term outcomes in relapse-onset multiple sclerosis. Brain 142, 2276–2287 (2019).
pubmed: 31342055
doi: 10.1093/brain/awz156
Kuhle, J. et al. Conversion from clinically isolated syndrome to multiple sclerosis: a large multicentre study. Mult. Scler. 21, 1013–1024 (2015).
pubmed: 25680984
doi: 10.1177/1352458514568827
Jacobs, L. D. et al. Intramuscular interferon beta-1a therapy initiated during a first demyelinating event in multiple sclerosis. CHAMPS Study Group. N. Engl. J. Med. 343, 898–904 (2000).
pubmed: 11006365
doi: 10.1056/NEJM200009283431301
Comi, G. et al. Effect of early interferon treatment on conversion to definite multiple sclerosis: a randomised study. Lancet 357, 1576–1582 (2001).
pubmed: 11377645
doi: 10.1016/S0140-6736(00)04725-5
Comi, G. et al. Effect of glatiramer acetate on conversion to clinically definite multiple sclerosis in patients with clinically isolated syndrome (PreCISe study): a randomised, double-blind, placebo-controlled trial. Lancet 374, 1503–1511 (2009).
pubmed: 19815268
doi: 10.1016/S0140-6736(09)61259-9
Linnerbauer, M. & Rothhammer, V. Protective functions of reactive astrocytes following central nervous system insult. Front. Immunol. 11, 573256 (2020).
pubmed: 33117368
pmcid: 7561408
doi: 10.3389/fimmu.2020.573256
Hohlfeld, R. Neurotrophic cross-talk between the nervous and immune systems: relevance for repair strategies in multiple sclerosis? J. Neurol. Sci. 265, 93–96 (2008).
pubmed: 17459415
doi: 10.1016/j.jns.2007.03.012
Dao, D. T., Anez-Bustillos, L., Adam, R. M., Puder, M. & Bielenberg, D. R. Heparin-binding epidermal growth factor-like growth factor as a critical mediator of tissue repair and regeneration. Am. J. Pathol. 188, 2446–2456 (2018).
pubmed: 30142332
pmcid: 6207098
doi: 10.1016/j.ajpath.2018.07.016
Jin, K. et al. Heparin-binding epidermal growth factor-like growth factor: hypoxia-inducible expression in vitro and stimulation of neurogenesis in vitro and in vivo. J. Neurosci. 22, 5365–5373 (2002).
pubmed: 12097488
pmcid: 6758221
doi: 10.1523/JNEUROSCI.22-13-05365.2002
Oyagi, A. et al. Forebrain specific heparin-binding epidermal growth factor-like growth factor knockout mice show exacerbated ischemia and reperfusion injury. Neuroscience 185, 116–124 (2011).
pubmed: 21524692
doi: 10.1016/j.neuroscience.2011.04.034
Filippi, M. et al. Intracortical lesions: relevance for new MRI diagnostic criteria for multiple sclerosis. Neurology 75, 1988–1994 (2010).
pubmed: 21115953
doi: 10.1212/WNL.0b013e3181ff96f6
Liddelow, S. A. et al. Neurotoxic reactive astrocytes are induced by activated microglia. Nature 541, 481–487 (2017).
pubmed: 28099414
pmcid: 5404890
doi: 10.1038/nature21029
Sanmarco, L. M. et al. Gut-licensed IFNγ
pubmed: 33408417
pmcid: 8039910
doi: 10.1038/s41586-020-03116-4
Berard, J. L., Wolak, K., Fournier, S. & David, S. Characterization of relapsing–remitting and chronic forms of experimental autoimmune encephalomyelitis in C57BL/6 mice. Glia 58, 434–445 (2010).
pubmed: 19780195
doi: 10.1002/glia.20935
Wheeler, M. A. et al. MAFG-driven astrocytes promote CNS inflammation. Nature 578, 593–599 (2020).
pubmed: 32051591
pmcid: 8049843
doi: 10.1038/s41586-020-1999-0
Tusher, V. G., Tibshirani, R. & Chu, G. Significance analysis of microarrays applied to the ionizing radiation response. Proc. Natl Acad. Sci. USA 98, 5116–5121 (2001).
pubmed: 11309499
pmcid: 33173
doi: 10.1073/pnas.091062498
Valentin-Torres, A. et al. Sustained TNF production by central nervous system infiltrating macrophages promotes progressive autoimmune encephalomyelitis. J. Neuroinflammation 13, 46 (2016).
pubmed: 26906225
pmcid: 4763407
doi: 10.1186/s12974-016-0513-y
Lin, C.-C. & Edelson, B. T. New insights into the role of IL-1β in experimental autoimmune encephalomyelitis and multiple sclerosis. J. Immunol. 198, 4553–4560 (2017).
pubmed: 28583987
doi: 10.4049/jimmunol.1700263
Mandl, M., Lieberum, M.-K. & Depping, R. A HIF-1α-driven feed-forward loop augments HIF signalling in Hep3B cells by upregulation of ARNT. Cell Death Dis. 7, e2284 (2016).
pubmed: 27362802
pmcid: 5108338
doi: 10.1038/cddis.2016.187
Vorrink, S. U. & Domann, F. E. Regulatory crosstalk and interference between the xenobiotic and hypoxia sensing pathways at the AhR-ARNT-HIF1α signaling node. Chem. Biol. Interact. 0, 82–88 (2014).
pmcid: 4091760
doi: 10.1016/j.cbi.2014.05.001
Chan, W. K., Yao, G., Gu, Y.-Z. & Bradfield, C. A. Cross-talk between the Aryl hydrocarbon receptor and hypoxia inducible factor signaling pathways: demonstration of competition and compensation. J. Biol. Chem. 274, 12115–12123 (1999).
pubmed: 10207038
doi: 10.1074/jbc.274.17.12115
Linnerbauer, M., Wheeler, M. A. & Quintana, F. J. Astrocyte crosstalk in CNS inflammation. Neuron 108, 608–622 (2020).
pubmed: 32898475
pmcid: 7704785
doi: 10.1016/j.neuron.2020.08.012
Browaeys, R., Saelens, W. & Saeys, Y. NicheNet: modeling intercellular communication by linking ligands to target genes. Nat. Methods 17, 159–162 (2020).
pubmed: 31819264
doi: 10.1038/s41592-019-0667-5
Foo, L. C. et al. Development of a novel method for the purification and culture of rodent astrocytes. Neuron 71, 799–811 (2011).
pubmed: 21903074
pmcid: 3172573
doi: 10.1016/j.neuron.2011.07.022
Puschmann, T. B. et al. HB-EGF affects astrocyte morphology, proliferation, differentiation, and the expression of intermediate filament proteins. J. Neurochem. 128, 878–889 (2014).
pubmed: 24188029
doi: 10.1111/jnc.12519
Bartus, K. et al. ErbB receptor signaling directly controls oligodendrocyte progenitor cell transformation and spontaneous remyelination after spinal cord injury. Glia 67, 1036–1046 (2019).
pubmed: 30637799
pmcid: 6491970
doi: 10.1002/glia.23586
Kaufmann, M. et al. Identification of early neurodegenerative pathways in progressive multiple sclerosis. Nat. Neurosci. 25, 944–955 (2022).
pubmed: 35726057
doi: 10.1038/s41593-022-01097-3
Opanashuk, L. A. et al. Heparin-binding epidermal growth factor-like growth factor in hippocampus: modulation of expression by seizures and anti-excitotoxic action. J. Neurosci. 19, 133–146 (1999).
pubmed: 9870945
pmcid: 6782387
doi: 10.1523/JNEUROSCI.19-01-00133.1999
Rothhammer, V. et al. Type I interferons and microbial metabolites of tryptophan modulate astrocyte activity and central nervous system inflammation via the aryl hydrocarbon receptor. Nat. Med. 22, 586–597 (2016).
pubmed: 27158906
pmcid: 4899206
doi: 10.1038/nm.4106
Ross, T. M. et al. Intranasal administration of interferon beta bypasses the blood-brain barrier to target the central nervous system and cervical lymph nodes: a non-invasive treatment strategy for multiple sclerosis. J. Neuroimmunol. 151, 66–77 (2004).
pubmed: 15145605
doi: 10.1016/j.jneuroim.2004.02.011
Ransohoff, R. M. Animal models of multiple sclerosis: the good, the bad and the bottom line. Nat. Neurosci. 15, 1074–1077 (2012).
pubmed: 22837037
pmcid: 7097342
doi: 10.1038/nn.3168
Kular, L. et al. DNA methylation changes in glial cells of the normal-appearing white matter in multiple sclerosis patients. Epigenetics 17, 1311–1330 (2022).
pubmed: 35094644
pmcid: 9586622
doi: 10.1080/15592294.2021.2020436
Huynh, J. L. et al. Epigenome-wide differences in pathology-free regions of multiple sclerosis–affected brains. Nat. Neurosci. 17, 121–130 (2014).
pubmed: 24270187
doi: 10.1038/nn.3588
Oh, J. & Bar-Or, A. Emerging therapies to target CNS pathophysiology in multiple sclerosis. Nat. Rev. Neurol. 18, 466–475 (2022).
pubmed: 35697862
doi: 10.1038/s41582-022-00675-0
Healy, L. M., Stratton, J. A., Kuhlmann, T. & Antel, J. The role of glial cells in multiple sclerosis disease progression. Nat. Rev. Neurol. 18, 237–248 (2022).
pubmed: 35190704
doi: 10.1038/s41582-022-00624-x
Kuhlmann, T., Lingfeld, G., Bitsch, A., Schuchardt, J. & Brück, W. Acute axonal damage in multiple sclerosis is most extensive in early disease stages and decreases over time. Brain 125, 2202–2212 (2002).
pubmed: 12244078
doi: 10.1093/brain/awf235
Elkjaer, M. L. et al. CSF proteome in multiple sclerosis subtypes related to brain lesion transcriptomes. Sci. Rep. 11, 4132 (2021).
pubmed: 33603109
pmcid: 7892884
doi: 10.1038/s41598-021-83591-5
Schenk, G. J. et al. Roles for HB-EGF and CD9 in multiple sclerosis. Glia 61, 1890–1905 (2013).
pubmed: 24038577
doi: 10.1002/glia.22565
Hoffmann, F. S. et al. Fingolimod induces neuroprotective factors in human astrocytes. J. Neuroinflammation 12, 184 (2015).
pubmed: 26419927
pmcid: 4589103
doi: 10.1186/s12974-015-0393-6
Jacob, A. et al. Hypoxia interferes with aryl hydrocarbon receptor pathway in hCMEC/D3 human cerebral microvascular endothelial cells. J. Neurochem. 132, 373–383 (2015).
pubmed: 25327972
doi: 10.1111/jnc.12972
Lassmann, H. Hypoxia-like tissue injury as a component of multiple sclerosis lesions. J. Neurol. Sci. 206, 187–191 (2003).
pubmed: 12559509
doi: 10.1016/S0022-510X(02)00421-5
Halder, S. K. & Milner, R. Chronic mild hypoxia accelerates recovery from preexisting EAE by enhancing vascular integrity and apoptosis of infiltrated monocytes. Proc. Natl Acad. Sci. USA 117, 11126–11135 (2020).
pubmed: 32371484
pmcid: 7245138
doi: 10.1073/pnas.1920935117
Chan, M. W. Y. et al. Low-dose 5-aza-2′-deoxycytidine pretreatment inhibits experimental autoimmune encephalomyelitis by induction of regulatory T cells. Mol. Med. 20, 248–256 (2014).
pubmed: 24869907
pmcid: 4107100
doi: 10.2119/molmed.2013.00159
Mangano, K. et al. Hypomethylating agent 5-aza-2′-deoxycytidine (DAC) ameliorates multiple sclerosis in mouse models. J. Cell. Physiol. 229, 1918–1925 (2014).
pubmed: 24700487
doi: 10.1002/jcp.24641
Scafidi, J. et al. Intranasal epidermal growth factor treatment rescues neonatal brain injury. Nature 506, 230–234 (2014).
pubmed: 24390343
doi: 10.1038/nature12880
Sandelin, A., Alkema, W., Engström, P., Wasserman, W. W. & Lenhard, B. JASPAR: an open-access database for eukaryotic transcription factor binding profiles. Nucleic Acids Res. 32, D91–D94 (2004).
pubmed: 14681366
pmcid: 308747
doi: 10.1093/nar/gkh012
Linnerbauer, M. et al. PD-L1 positive astrocytes attenuate inflammatory functions of PD-1 positive microglia in models of autoimmune neuroinflammation. Nat. Commun. 14, 5555 (2023).
pubmed: 37689786
pmcid: 10492803
doi: 10.1038/s41467-023-40982-8
Clark, I. C. et al. Barcoded viral tracing of single-cell interactions in central nervous system inflammation. Science 372, eabf1230 (2021).
pubmed: 33888612
pmcid: 8157482
doi: 10.1126/science.abf1230
Linnerbauer, M. et al. Astrocyte-derived pleiotrophin mitigates late-stage autoimmune CNS inflammation. Front. Immunol. 12, 800128 (2022).
pubmed: 35046956
pmcid: 8762329
doi: 10.3389/fimmu.2021.800128
McCarthy, K. D. & de Vellis, J. Preparation of separate astroglial and oligodendroglial cell cultures from rat cerebral tissue. J. Cell Biol. 85, 890–902 (1980).
pubmed: 6248568
doi: 10.1083/jcb.85.3.890
Wagner, A. et al. Metabolic modeling of single Th17 cells reveals regulators of autoimmunity. Cell 184, 4168–4185.e21 (2021).
pubmed: 34216539
pmcid: 8621950
doi: 10.1016/j.cell.2021.05.045
Rothhammer, V. et al. Th17 lymphocytes traffic to the central nervous system independently of α4 integrin expression during EAE. J. Exp. Med. 208, 2465–2476 (2011).
pubmed: 22025301
pmcid: 3256959
doi: 10.1084/jem.20110434
Bosch-Queralt, M. et al. Diet-dependent regulation of TGFβ impairs reparative innate immune responses after demyelination. Nat. Metab. 3, 211–227 (2021).
pubmed: 33619376
pmcid: 7610359
doi: 10.1038/s42255-021-00341-7
Rothhammer, V. et al. Microglial control of astrocytes in response to microbial metabolites. Nature 557, 724–728 (2018).
pubmed: 29769726
pmcid: 6422159
doi: 10.1038/s41586-018-0119-x
Linnerbauer, M. et al. Intranasal delivery of a small-molecule ErbB inhibitor promotes recovery from acute and late-stage CNS inflammation. JCI Insight 7, e154824 (2022).
pubmed: 35393953
pmcid: 9057609
doi: 10.1172/jci.insight.154824
Wolf, I. et al. The Medical Imaging Interaction Toolkit. Med. Image Anal. 9, 594–604 (2005).
pubmed: 15896995
doi: 10.1016/j.media.2005.04.005
Tsaktanis, T. et al. Aryl hydrocarbon receptor plasma agonist activity correlates with disease activity in progressive MS. Neurol. Neuroimmunol. Neuroinflamm. 8, e933 (2021).
pubmed: 33361385
doi: 10.1212/NXI.0000000000000933
Untergasser, A. et al. Primer3—new capabilities and interfaces. Nucleic Acids Res. 40, e115 (2012).
pubmed: 22730293
pmcid: 3424584
doi: 10.1093/nar/gks596
Ewels, P. A. et al. The nf-core framework for community-curated bioinformatics pipelines. Nat. Biotechnol. 38, 276–278 (2020).
pubmed: 32055031
doi: 10.1038/s41587-020-0439-x
Ritchie, M. E. et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 43, e47 (2015).
pubmed: 25605792
pmcid: 4402510
doi: 10.1093/nar/gkv007
Moore, J. E. et al. Expanded encyclopaedias of DNA elements in the human and mouse genomes. Nature 583, 699–710 (2020).
pubmed: 32728249
pmcid: 7410828
doi: 10.1038/s41586-020-2493-4
Navarro Gonzalez, J. et al. The UCSC Genome Browser database: 2021 update. Nucleic Acids Res. 49, D1046–D1057 (2021).
pubmed: 33221922
doi: 10.1093/nar/gkaa1070
Hahne, F. & Ivanek, R. Visualizing genomic data using Gviz and Bioconductor. Methods Mol. Biol. 1418, 335–351 (2016).
pubmed: 27008022
doi: 10.1007/978-1-4939-3578-9_16
Morris, T. J. et al. ChAMP: 450k chip analysis methylation pipeline. Bioinformatics 30, 428–430 (2014).
pubmed: 24336642
doi: 10.1093/bioinformatics/btt684
Aryee, M. J. et al. Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays. Bioinformatics 30, 1363–1369 (2014).
pubmed: 24478339
pmcid: 4016708
doi: 10.1093/bioinformatics/btu049
McCartney, D. L. et al. Identification of polymorphic and off-target probe binding sites on the Illumina Infinium MethylationEPIC BeadChip. Genom. Data 9, 22–24 (2016).
pubmed: 27330998
pmcid: 4909830
doi: 10.1016/j.gdata.2016.05.012
Pidsley, R. et al. Critical evaluation of the Illumina MethylationEPIC BeadChip microarray for whole-genome DNA methylation profiling. Genome Biol. 17, 208 (2016).
pubmed: 27717381
pmcid: 5055731
doi: 10.1186/s13059-016-1066-1
Nordlund, J. et al. Genome-wide signatures of differential DNA methylation in pediatric acute lymphoblastic leukemia. Genome Biol. 14, r105 (2013).
pubmed: 24063430
pmcid: 4014804
doi: 10.1186/gb-2013-14-9-r105
Chen, Y. et al. Discovery of cross-reactive probes and polymorphic CpGs in the Illumina Infinium HumanMethylation450 microarray. Epigenetics 8, 203–209 (2013).
pubmed: 23314698
pmcid: 3592906
doi: 10.4161/epi.23470
Johnson, W. E., Li, C. & Rabinovic, A. Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics 8, 118–127 (2007).
pubmed: 16632515
doi: 10.1093/biostatistics/kxj037
Houseman, E. A., Molitor, J. & Marsit, C. J. Reference-free cell mixture adjustments in analysis of DNA methylation data. Bioinformatics 30, 1431–1439 (2014).
pubmed: 24451622
pmcid: 4016702
doi: 10.1093/bioinformatics/btu029
Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA 102, 15545–15550 (2005).
pubmed: 16199517
pmcid: 1239896
doi: 10.1073/pnas.0506580102
Mootha, V. K. et al. PGC-1α-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes. Nat. Genet. 34, 267–273 (2003).
pubmed: 12808457
doi: 10.1038/ng1180
Mi, H. et al. Protocol update for large-scale genome and gene function analysis with PANTHER classification system (v.14.0). Nat. Protoc. 14, 703–721 (2019).
pubmed: 30804569
pmcid: 6519457
doi: 10.1038/s41596-019-0128-8
Hao, Y. et al. Integrated analysis of multimodal single-cell data. Cell 184, 3573–3587.e29 (2021).
pubmed: 34062119
pmcid: 8238499
doi: 10.1016/j.cell.2021.04.048
Chen, E. Y. et al. Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool. BMC Bioinformatics 14, 128 (2013).
pubmed: 23586463
pmcid: 3637064
doi: 10.1186/1471-2105-14-128
Cao, J. et al. A human cell atlas of fetal gene expression. Science 370, eaba7721 (2020).
pubmed: 33184181
pmcid: 7780123
doi: 10.1126/science.aba7721