BHLHE40/41 regulate microglia and peripheral macrophage responses associated with Alzheimer's disease and other disorders of lipid-rich tissues.


Journal

Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555

Informations de publication

Date de publication:
06 Mar 2024
Historique:
received: 10 02 2023
accepted: 16 02 2024
medline: 8 3 2024
pubmed: 7 3 2024
entrez: 6 3 2024
Statut: epublish

Résumé

Genetic and experimental evidence suggests that Alzheimer's disease (AD) risk alleles and genes may influence disease susceptibility by altering the transcriptional and cellular responses of macrophages, including microglia, to damage of lipid-rich tissues like the brain. Recently, sc/nRNA sequencing studies identified similar transcriptional activation states in subpopulations of macrophages in aging and degenerating brains and in other diseased lipid-rich tissues. We collectively refer to these subpopulations of microglia and peripheral macrophages as DLAMs. Using macrophage sc/nRNA-seq data from healthy and diseased human and mouse lipid-rich tissues, we reconstructed gene regulatory networks and identified 11 strong candidate transcriptional regulators of the DLAM response across species. Loss or reduction of two of these transcription factors, BHLHE40/41, in iPSC-derived microglia and human THP-1 macrophages as well as loss of Bhlhe40/41 in mouse microglia, resulted in increased expression of DLAM genes involved in cholesterol clearance and lysosomal processing, increased cholesterol efflux and storage, and increased lysosomal mass and degradative capacity. These findings provide targets for therapeutic modulation of macrophage/microglial function in AD and other disorders affecting lipid-rich tissues.

Identifiants

pubmed: 38448474
doi: 10.1038/s41467-024-46315-7
pii: 10.1038/s41467-024-46315-7
pmc: PMC10917780
doi:

Substances chimiques

Cholesterol 97C5T2UQ7J
Lipids 0
BHLHE40 protein, human 0
Homeodomain Proteins 0
Basic Helix-Loop-Helix Transcription Factors 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

2058

Subventions

Organisme : NIA NIH HHS
ID : RF1 AG054011
Pays : United States
Organisme : NIH HHS
ID : S10 OD026880
Pays : United States
Organisme : NIA NIH HHS
ID : R56 AG081417
Pays : United States
Organisme : NIA NIH HHS
ID : U01 AG066757
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR004419
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL153712
Pays : United States
Organisme : NIH HHS
ID : S10 OD030463
Pays : United States
Organisme : NIA NIH HHS
ID : U01 AG058635
Pays : United States

Commentaires et corrections

Type : UpdateOf

Informations de copyright

© 2024. The Author(s).

Références

Morioka, S., Maueröder, C. & Ravichandran, K. S. Living on the edge: efferocytosis at the interface of homeostasis and pathology. Immunity 50, 1149–1162 (2019).
pubmed: 31117011 pmcid: 6721617 doi: 10.1016/j.immuni.2019.04.018
Nott, A. et al. Brain cell type-specific enhancer-promoter interactome maps and disease-risk association. Science 366, 1134–1139 (2019).
pubmed: 31727856 pmcid: 7028213 doi: 10.1126/science.aay0793
Doran, A. C., Yurdagul, A. Jr & Tabas, I. Efferocytosis in health and disease. Nat. Rev. Immunol. 20, 254–267 (2020).
pubmed: 31822793 doi: 10.1038/s41577-019-0240-6
Novikova, G. et al. Integration of Alzheimer’s disease genetics and myeloid genomics identifies disease risk regulatory elements and genes. Nat. Commun. 12, 1610 (2021).
pubmed: 33712570 pmcid: 7955030 doi: 10.1038/s41467-021-21823-y
Boada-Romero, E., Martinez, J., Heckmann, B. L. & Green, D. R. The clearance of dead cells by efferocytosis. Nat. Rev. Mol. Cell Biol. 21, 398–414 (2020).
pubmed: 32251387 pmcid: 7392086 doi: 10.1038/s41580-020-0232-1
Jaitin, D. A. et al. Lipid-associated macrophages control metabolic homeostasis in a Trem2-dependent manner. Cell 178, 686–698.e14 (2019).
pubmed: 31257031 pmcid: 7068689 doi: 10.1016/j.cell.2019.05.054
Björkhem, I. & Meaney, S. Brain cholesterol: long secret life behind a barrier. Arterioscler. Thromb. Vasc. Biol. 24, 806–815 (2004).
pubmed: 14764421 doi: 10.1161/01.ATV.0000120374.59826.1b
Keren-Shaul, H. et al. A unique microglia type associated with restricting development of Alzheimer’s disease. Cell 169, 1276–1290.e17 (2017).
pubmed: 28602351 doi: 10.1016/j.cell.2017.05.018
Cochain, C. et al. Single-cell RNA-Seq reveals the transcriptional landscape and heterogeneity of aortic macrophages in murine atherosclerosis. Circ. Res. 122, 1661–1674 (2018).
pubmed: 29545365 doi: 10.1161/CIRCRESAHA.117.312509
Fernandez, D. M. et al. Single-cell immune landscape of human atherosclerotic plaques. Nat. Med. 25, 1576–1588 (2019).
pubmed: 31591603 pmcid: 7318784 doi: 10.1038/s41591-019-0590-4
Podleśny-Drabiniok, A., Marcora, E. & Goate, A. M. Microglial phagocytosis: a disease-associated process emerging from Alzheimer’s disease genetics. Trends Neurosci. 43, 965–979 (2020).
pubmed: 33127097 pmcid: 9080913 doi: 10.1016/j.tins.2020.10.002
Romero-Molina, C., Garretti, F., Andrews, S. J., Marcora, E. & Goate, A. M. Microglial efferocytosis: diving into the Alzheimer’s disease gene pool. Neuron 110, 3513–3533 (2022).
pubmed: 36327897 doi: 10.1016/j.neuron.2022.10.015
Krasemann, S. et al. The TREM2-APOE pathway drives the transcriptional phenotype of dysfunctional microglia in neurodegenerative diseases. Immunity 47, 566–581.e9 (2017).
pubmed: 28930663 pmcid: 5719893 doi: 10.1016/j.immuni.2017.08.008
Nugent, A. A. et al. TREM2 regulates microglial cholesterol metabolism upon chronic phagocytic challenge. Neuron 105, 837–854.e9 (2020).
pubmed: 31902528 doi: 10.1016/j.neuron.2019.12.007
Andreone, B. J. et al. Alzheimer’s-associated PLCγ2 is a signaling node required for both TREM2 function and the inflammatory response in human microglia. Nat. Neurosci. 23, 927–938 (2020).
pubmed: 32514138 doi: 10.1038/s41593-020-0650-6
Fletcher, M. N. C. et al. Master regulators of FGFR2 signalling and breast cancer risk. Nat. Commun. 4, 2464 (2013).
pubmed: 24043118 doi: 10.1038/ncomms3464
Rangaraju, S. et al. Identification and therapeutic modulation of a pro-inflammatory subset of disease-associated-microglia in Alzheimer’s disease. Mol. Neurodegener. 13, 24 (2018).
pubmed: 29784049 pmcid: 5963076 doi: 10.1186/s13024-018-0254-8
Gao, T. et al. Transcriptional regulation of homeostatic and disease-associated-microglial genes by IRF1, LXRβ, and CEBPα. Glia 67, 1958–1975 (2019).
pubmed: 31301160 pmcid: 7190149 doi: 10.1002/glia.23678
Friedman, B. A. et al. Diverse brain myeloid expression profiles reveal distinct microglial activation states and aspects of Alzheimer’s disease not evident in mouse models. Cell Rep. 22, 832–847 (2018).
pubmed: 29346778 doi: 10.1016/j.celrep.2017.12.066
MacParland, S. A. et al. Single cell RNA sequencing of human liver reveals distinct intrahepatic macrophage populations. Nat. Commun. 9, 4383 (2018).
pubmed: 30348985 pmcid: 6197289 doi: 10.1038/s41467-018-06318-7
Ramachandran, P. et al. Resolving the fibrotic niche of human liver cirrhosis at single-cell level. Nature 575, 512–518 (2019).
pubmed: 31597160 pmcid: 6876711 doi: 10.1038/s41586-019-1631-3
Zhou, Y. et al. Human and mouse single-nucleus transcriptomics reveal TREM2-dependent and TREM2-independent cellular responses in Alzheimer’s disease. Nat. Med. 26, 131–142 (2020).
pubmed: 31932797 pmcid: 6980793 doi: 10.1038/s41591-019-0695-9
Mathys, H. et al. Single-cell transcriptomic analysis of Alzheimer’s disease. Nature 570, 332–337 (2019).
pubmed: 31042697 pmcid: 6865822 doi: 10.1038/s41586-019-1195-2
Mancuso, R. et al. Stem-cell-derived human microglia transplanted in mouse brain to study human disease. Nat. Neurosci. 22, 2111–2116 (2019).
pubmed: 31659342 doi: 10.1038/s41593-019-0525-x
Olah, M. et al. Single-cell RNA sequencing of human microglia uncovers a subset associated with Alzheimer’s disease. Nat. Commun. 11, 6129 (2020).
pubmed: 33257666 pmcid: 7704703 doi: 10.1038/s41467-020-19737-2
Xiong, X. et al. Landscape of intercellular crosstalk in healthy and NASH liver revealed by single-cell secretome gene analysis. Mol. Cell 75, 644–660.e5 (2019).
pubmed: 31398325 pmcid: 7262680 doi: 10.1016/j.molcel.2019.07.028
Lin, J.-D. et al. Single-cell analysis of fate-mapped macrophages reveals heterogeneity, including stem-like properties, during atherosclerosis progression and regression. JCI Insight 4, e124574 (2019).
pubmed: 30830865 pmcid: 6478411 doi: 10.1172/jci.insight.124574
Frigerio, C. S. et al. The major risk factors for Alzheimer’s disease: age, sex, and genes modulate the microglia response to Aβ plaques. Cell Rep. 27, 1293–1306.e6 (2019).
pmcid: 7340153 doi: 10.1016/j.celrep.2019.03.099
Ximerakis, M. et al. Single-cell transcriptomic profiling of the aging mouse brain. Nat. Neurosci. 22, 1696–1708 (2019).
pubmed: 31551601 doi: 10.1038/s41593-019-0491-3
Margolin, A. A. et al. ARACNE: an algorithm for the reconstruction of gene regulatory networks in a mammalian cellular context. BMC Bioinforma. 7, S7 (2006).
doi: 10.1186/1471-2105-7-S1-S7
Gosselin, D. et al. An environment-dependent transcriptional network specifies human microglia identity. Science 356, eaal3222 (2017).
Dolan, M.-J. et al. Exposure of iPSC-derived human microglia to brain substrates enables the generation and manipulation of diverse transcriptional states in vitro. Nat. Immunol. 24, 1382–1390 (2023).
pubmed: 37500887 pmcid: 10382323 doi: 10.1038/s41590-023-01558-2
Huang, K.-L. et al. A common haplotype lowers PU.1 expression in myeloid cells and delays onset of Alzheimer’s disease. Nat. Neurosci. 20, 1052–1061 (2017).
pubmed: 28628103 pmcid: 5759334 doi: 10.1038/nn.4587
Rustenhoven, J. et al. PU.1 regulates Alzheimer’s disease-associated genes in primary human microglia. Mol. Neurodegen. 13, 44 (2018).
doi: 10.1186/s13024-018-0277-1
Kosoy, R. et al. Genetics of the human microglia regulome refines Alzheimer’s disease risk loci. Nat. Genet. 54, 1145–1154 (2022).
pubmed: 35931864 pmcid: 9388367 doi: 10.1038/s41588-022-01149-1
Heinz, S. et al. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol. Cell 38, 576–589 (2010).
pubmed: 20513432 pmcid: 2898526 doi: 10.1016/j.molcel.2010.05.004
Kunkle, B. W. et al. Novel Alzheimer disease risk loci and pathways in african american individuals using the african genome resources panel: a meta-analysis. JAMA Neurol. https://doi.org/10.1001/jamaneurol.2020.3536 (2020).
Cho, Y. et al. The basic helix-loop-helix proteins differentiated embryo chondrocyte (DEC) 1 and DEC2 function as corepressors of retinoid X receptors. Mol. Pharmacol. 76, 1360–1369 (2009).
pubmed: 19786558 doi: 10.1124/mol.109.057000
Carey, K. L. et al. TFEB transcriptional responses reveal negative feedback by BHLHE40 and BHLHE41. Cell Rep. 33, 108371 (2020).
pubmed: 33176151 pmcid: 7686957 doi: 10.1016/j.celrep.2020.108371
Noshiro, M. et al. DEC1 regulates the rhythmic expression of PPARγ target genes involved in lipid metabolism in white adipose tissue. Genes Cells 25, 232–241 (2020).
pubmed: 31991027 doi: 10.1111/gtc.12752
Ow, J. R., Tan, Y. H., Jin, Y., Bahirvani, A. G. & Taneja, R. Stra13 and Sharp-1, the non-grouchy regulators of development and disease. Curr. Top. Dev. Biol. 110, 317–338 (2014).
pubmed: 25248481 doi: 10.1016/B978-0-12-405943-6.00009-9
Baier, P. C. et al. Mice lacking the circadian modulators SHARP1 and SHARP2 display altered sleep and mixed-state endophenotypes of psychiatric disorders. PLoS One 9, e110310 (2014).
pubmed: 25340473 pmcid: 4207740 doi: 10.1371/journal.pone.0110310
Honma, S. et al. Dec1 and Dec2 are regulators of the mammalian molecular clock. Nature 419, 841–844 (2002).
pubmed: 12397359 doi: 10.1038/nature01123
Spitz, F. & Furlong, E. E. M. Transcription factors: from enhancer binding to developmental control. Nat. Rev. Genet. 13, 613–626 (2012).
pubmed: 22868264 doi: 10.1038/nrg3207
Lau, S.-F. et al. IL-33-PU.1 transcriptome reprogramming drives functional state transition and clearance activity of microglia in Alzheimer’s disease. Cell Rep. 31, 107530 (2020).
pubmed: 32320664 doi: 10.1016/j.celrep.2020.107530
Pimenova, A. A. et al. Alzheimer’s-associated PU.1 expression levels regulate microglial inflammatory response. Neurobiol. Dis. 148, 105217 (2021).
pubmed: 33301878 doi: 10.1016/j.nbd.2020.105217
Jones, R. E., Andrews, R., Holmans, P., Hill, M. & Taylor, P. R. Modest changes in Spi1 dosage reveal the potential for altered microglial function as seen in Alzheimer’s disease. Sci. Rep. 11, 14935 (2021).
pubmed: 34294785 pmcid: 8298495 doi: 10.1038/s41598-021-94324-z
Zia, S. et al. Single-cell microglial transcriptomics during demyelination defines a microglial state required for lytic carcass clearance. Mol. Neurodegener. 17, 82 (2022).
pubmed: 36514132 pmcid: 9746011 doi: 10.1186/s13024-022-00584-2
Krämer, A., Green, J., Pollard, J. Jr & Tugendreich, S. Causal analysis approaches in Ingenuity Pathway Analysis. Bioinformatics 30, 523–530 (2014).
pubmed: 24336805 doi: 10.1093/bioinformatics/btt703
Yang, M. et al. Emerging roles and regulation of MiT/TFE transcriptional factors. Cell Commun. Signal. 16, 31 (2018).
pubmed: 29903018 pmcid: 6003119 doi: 10.1186/s12964-018-0242-1
Laurette, P. et al. Transcription factor MITF and remodeller BRG1 define chromatin organisation at regulatory elements in melanoma cells. Elife 4, e06857 (2015).
pubmed: 25803486 pmcid: 4407272 doi: 10.7554/eLife.06857
McQuade, A. et al. Development and validation of a simplified method to generate human microglia from pluripotent stem cells. Mol. Neurodegener. 13, 67 (2018).
pubmed: 30577865 pmcid: 6303871 doi: 10.1186/s13024-018-0297-x
Plaisier, S. B., Taschereau, R., Wong, J. A. & Graeber, T. G. Rank–rank hypergeometric overlap: identification of statistically significant overlap between gene-expression signatures. Nucleic Acids Res. 38, e169–e169 (2010).
pubmed: 20660011 pmcid: 2943622 doi: 10.1093/nar/gkq636
Cahill, K. M., Huo, Z., Tseng, G. C., Logan, R. W. & Seney, M. L. Improved identification of concordant and discordant gene expression signatures using an updated rank-rank hypergeometric overlap approach. Sci. Rep. 8, 9588 (2018).
pubmed: 29942049 pmcid: 6018631 doi: 10.1038/s41598-018-27903-2
Gerrits, E. et al. Distinct amyloid-β and tau-associated microglia profiles in Alzheimer’s disease. Acta Neuropathol. 141, 681–696 (2021).
pubmed: 33609158 pmcid: 8043951 doi: 10.1007/s00401-021-02263-w
Claes, C. et al. Plaque-associated human microglia accumulate lipid droplets in a chimeric model of Alzheimer’s disease. Mol. Neurodegen. 16, 50 (2021).
doi: 10.1186/s13024-021-00473-0
Hasselmann, J. et al. Development of a chimeric model to study and manipulate human microglia in vivo. Neuron 103, 1016–1033.e10 (2019).
pubmed: 31375314 pmcid: 7138101 doi: 10.1016/j.neuron.2019.07.002
Moore, K. J. & Tabas, I. Macrophages in the pathogenesis of atherosclerosis. Cell 145, 341–355 (2011).
pubmed: 21529710 pmcid: 3111065 doi: 10.1016/j.cell.2011.04.005
Rauschmeier, R. et al. Bhlhe40 and Bhlhe41 transcription factors regulate alveolar macrophage self-renewal and identity. EMBO J. 38, e101233 (2019).
pubmed: 31414712 pmcid: 6769426 doi: 10.15252/embj.2018101233
Marschallinger, J. et al. Lipid-droplet-accumulating microglia represent a dysfunctional and proinflammatory state in the aging brain. Nat. Neurosci. 23, 194–208 (2020).
pubmed: 31959936 pmcid: 7595134 doi: 10.1038/s41593-019-0566-1
Spann, N. J. et al. Regulated accumulation of desmosterol integrates macrophage lipid metabolism and inflammatory responses. Cell 151, 138–152 (2012).
pubmed: 23021221 pmcid: 3464914 doi: 10.1016/j.cell.2012.06.054
Feige, E. et al. Hypoxia-induced transcriptional repression of the melanoma-associated oncogene MITF. Proc. Natl Acad. Sci. USA 108, E924–E933 (2011).
pubmed: 21949374 pmcid: 3203758 doi: 10.1073/pnas.1106351108
Kamphuis, W., Kooijman, L., Schetters, S., Orre, M. & Hol, E. M. Transcriptional profiling of CD11c-positive microglia accumulating around amyloid plaques in a mouse model for Alzheimer’s disease. Biochim. Biophys. Acta 1862, 1847–1860 (2016).
pubmed: 27425031 doi: 10.1016/j.bbadis.2016.07.007
Stehling-Sun, S., Dade, J., Nutt, S. L., DeKoter, R. P. & Camargo, F. D. Regulation of lymphoid versus myeloid fate’ choice’ by the transcription factor Mef2c. Nat. Immunol. 10, 289–296 (2009).
pubmed: 19169261 doi: 10.1038/ni.1694
Gosselin, D. et al. Environment drives selection and function of enhancers controlling tissue-specific macrophage identities. Cell 159, 1327–1340 (2014).
pubmed: 25480297 pmcid: 4364385 doi: 10.1016/j.cell.2014.11.023
Deczkowska, A. et al. Disease-associated microglia: a universal immune sensor of neurodegeneration. Cell 173, 1073–1081 (2018).
pubmed: 29775591 doi: 10.1016/j.cell.2018.05.003
Jonsson, T. et al. Variant of TREM2 associated with the risk of Alzheimer’s disease. N. Engl. J. Med. 368, 107–116 (2013).
pubmed: 23150908 doi: 10.1056/NEJMoa1211103
Wang, N. et al. Opposing effects of apoE2 and apoE4 on microglial activation and lipid metabolism in response to demyelination. Mol. Neurodegener. 17, 75 (2022).
pubmed: 36419137 pmcid: 9682675 doi: 10.1186/s13024-022-00577-1
Liu, C.-C. et al. Cell-autonomous effects of APOE4 in restricting microglial response in brain homeostasis and Alzheimer’s disease. Nat. Immunol. 24, 1854–1866 (2023).
pubmed: 37857825 doi: 10.1038/s41590-023-01640-9
Yin, Z. et al. APOE4 impairs the microglial response in Alzheimer’s disease by inducing TGFβ-mediated checkpoints. Nat. Immunol. 24, 1839–1853 (2023).
pubmed: 37749326 doi: 10.1038/s41590-023-01627-6
Lambert, J.-C. Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer’s disease. Nat. Genet. 45, 1452–1458 (2013).
pubmed: 24162737 pmcid: 3896259 doi: 10.1038/ng.2802
Kunkle, B. W. et al. Genetic meta-analysis of diagnosed Alzheimer’s disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing. Nat. Genet. 51, 414–430 (2019).
pubmed: 30820047 pmcid: 6463297 doi: 10.1038/s41588-019-0358-2
Hou, J., Chen, Y., Grajales-Reyes, G. & Colonna, M. TREM2 dependent and independent functions of microglia in Alzheimer’s disease. Mol. Neurodegener. 17, 84 (2022).
pubmed: 36564824 pmcid: 9783481 doi: 10.1186/s13024-022-00588-y
Seuter, S., Pehkonen, P., Heikkinen, S. & Carlberg, C. The gene for the transcription factor BHLHE40/DEC1/stra13 is a dynamically regulated primary target of the vitamin D receptor. J. Steroid Biochem. Mol. Biol. 136, 62–67 (2013).
pubmed: 23220548 doi: 10.1016/j.jsbmb.2012.11.011
Noshiro, M. et al. Liver X receptors (LXRalpha and LXRbeta) are potent regulators for hepatic Dec1 expression. Genes Cells 14, 29–40 (2009).
pubmed: 19032342 doi: 10.1111/j.1365-2443.2008.01247.x
Noshiro, M. et al. Deficiency of the basic helix-loop-helix transcription factor DEC1 prevents obesity induced by a high-fat diet in mice. Genes Cells 23, 658–669 (2018).
doi: 10.1111/gtc.12607
Gubern, A. et al. Lipid droplet biogenesis induced by stress involves triacylglycerol synthesis that depends on group VIA phospholipase A2. J. Biol. Chem. 284, 5697–5708 (2009).
pubmed: 19117952 doi: 10.1074/jbc.M806173200
Lee, J.-S., Mendez, R., Heng, H. H., Yang, Z.-Q. & Zhang, K. Pharmacological ER stress promotes hepatic lipogenesis and lipid droplet formation. Am. J. Transl. Res. 4, 102–113 (2012).
pubmed: 22347525 pmcid: 3276380
Nguyen, T. B. et al. DGAT1-dependent lipid droplet biogenesis protects mitochondrial function during starvation-induced autophagy. Dev. Cell 42, 9–21.e5 (2017).
pubmed: 28697336 pmcid: 5553613 doi: 10.1016/j.devcel.2017.06.003
Geltinger, F. et al. Friend or foe: lipid droplets as organelles for protein and lipid storage in cellular stress response, aging and disease. Molecules 25, 5053 (2020).
pubmed: 33143278 pmcid: 7663626 doi: 10.3390/molecules25215053
Williams, K. B. et al. LXR agonists promote lipid droplet formation in RPE cells. Investig. Ophthalmol. Vis. Sci. 61, 3114–3114 (2020).
Thrupp, N. et al. Single-nucleus RNA-Seq is not suitable for detection of microglial activation genes in humans. Cell Rep. 32, 108189 (2020).
pubmed: 32997994 pmcid: 7527779 doi: 10.1016/j.celrep.2020.108189
Chen, Y. & Colonna, M. Microglia in Alzheimer’s disease at single-cell level. Are there common patterns in humans and mice? J. Exp. Med. 218, e20202717 (2021).
pubmed: 34292312 pmcid: 8302448 doi: 10.1084/jem.20202717
Vlahos, L. et al. Systematic, protein activity-based characterization of single-cell state. bioRxiv 2021.05.20.445002. Preprint at https://doi.org/10.1101/2021.05.20.445002 (2023).
Obradovic, A. et al. Single-cell protein activity analysis identifies recurrence-associated renal tumor macrophages. Cell 184, 2988–3005.e16 (2021).
pubmed: 34019793 pmcid: 8479759 doi: 10.1016/j.cell.2021.04.038
Obradovic, A. et al. PISCES: a pipeline for the systematic, protein activity-based analysis of single-cell RNA sequencing data. bioRxiv 2021.05.20.445002. Preprint at https://doi.org/10.1101/2021.05.20.445002 (2021).
Durinck, S., Spellman, P. T., Birney, E. & Huber, W. Mapping identifiers for the integration of genomic datasets with the R/Bioconductor package biomaRt. Nat. Protoc. 4, 1184–1191 (2009).
pubmed: 19617889 pmcid: 3159387 doi: 10.1038/nprot.2009.97
Park, S. H. et al. Type I interferons and the cytokine TNF cooperatively reprogram the macrophage epigenome to promote inflammatory activation. Nat. Immunol. 18, 1104–1116 (2017).
pubmed: 28825701 pmcid: 5605457 doi: 10.1038/ni.3818
Daniel, B. et al. The transcription factor EGR2 is the molecular linchpin connecting STAT6 activation to the late, stable epigenomic program of alternative macrophage polarization. Genes Dev. https://doi.org/10.1101/gad.343038.120 (2020)
Leinonen, R., Sugawara, H. & Shumway, M. International Nucleotide Sequence Database Collaboration The sequence read archive. Nucleic Acids Res. 39, D19–D21 (2011).
pubmed: 21062823 doi: 10.1093/nar/gkq1019
Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).
pubmed: 22388286 pmcid: 3322381 doi: 10.1038/nmeth.1923
Andrews, S. & Others. FastQC: a quality control tool for high throughput sequence data. Preprint at (2010).
Li, H. et al. The sequence alignment/map format and SAM tools. Bioinformatics 25, 2078–2079 (2009).
pubmed: 19505943 pmcid: 2723002 doi: 10.1093/bioinformatics/btp352
Zhang, Y. et al. Model-based analysis of ChIP-Seq (MACS). Genome Biol. 9, R137 (2008).
pubmed: 18798982 pmcid: 2592715 doi: 10.1186/gb-2008-9-9-r137
Lawrence, M. et al. Software for computing and annotating genomic ranges. PLoS Comput. Biol. 9, e1003118 (2013).
pubmed: 23950696 pmcid: 3738458 doi: 10.1371/journal.pcbi.1003118
Finucane, H. K. et al. Partitioning heritability by functional annotation using genome-wide association summary statistics. Nat. Genet. 47, 1228–1235 (2015).
pubmed: 26414678 pmcid: 4626285 doi: 10.1038/ng.3404
Kreitzer, F. R. et al. A robust method to derive functional neural crest cells from human pluripotent stem cells. Am. J. Stem Cells 2, 119–131 (2013).
pubmed: 23862100 pmcid: 3708511
Hoffman, G. E. & Roussos, P. Dream: powerful differential expression analysis for repeated measures designs. Bioinformatics 37, 192–201 (2021).
pubmed: 32730587 doi: 10.1093/bioinformatics/btaa687
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
Huo, Z. Improved RRHO package. (Github, 2016).
Podlesny-Drabiniok, A., Novikova, G., et al. BHLHE40/41 regulate microglia and peripheral macrophage responses associated with Alzheimer’s disease and other disorders of lipid-rich tissues. marcoralab/bhlhe_manuscript: v1.0. https://doi.org/10.5281/zenodo.10516418 2024.

Auteurs

Anna Podleśny-Drabiniok (A)

Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.

Gloriia Novikova (G)

Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
OMNI Bioinformatics Department, Genentech, Inc., South San Francisco, CA, USA.

Yiyuan Liu (Y)

Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.

Josefine Dunst (J)

Department of Medicine, Division of Immunology and Allergy, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden.
Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.

Rose Temizer (R)

Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.

Chiara Giannarelli (C)

Department of Medicine, Division of Cardiology, NYU Cardiovascular Research Center, New York University School of Medicine, New York, NY, USA.
Department of Pathology, New York University School of Medicine, New York, NY, USA.

Samuele Marro (S)

Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.

Taras Kreslavsky (T)

Department of Medicine, Division of Immunology and Allergy, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden.
Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.

Edoardo Marcora (E)

Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA. edoardo.marcora@mssm.edu.
Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA. edoardo.marcora@mssm.edu.

Alison Mary Goate (AM)

Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA. alison.goate@mssm.edu.
Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA. alison.goate@mssm.edu.
Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA. alison.goate@mssm.edu.

Articles similaires

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female
Humans United States Aged Cross-Sectional Studies Medicare Part C
1.00
Humans Yoga Low Back Pain Female Male

Classifications MeSH