Author Correction: Single-cell transcriptomic analysis of Alzheimer’s disease (Nature, (2019), 570, 7761, (332-337), 10.1038/s41586-019-1195-2);Single-cell transcriptomic analysis of Alzheimer’s disease

Nature

Volumn 570, Issue 7761, 2019, Pages 332-337

  Mathys, Hansruedi ^a   Davila Velderrain, Jose ^b,c   Peng, Zhuyu ^a   Gao, Fan ^a   Mohammadi, Shahin ^b,c   Young, Jennie Z ^a   Menon, Madhvi ^c,d   He, Liang ^b,c   Abdurrob, Fatema ^a   Jiang, Xueqiao ^a   Martorell, Anthony J ^a   Ransohoff, Richard M ^e   Hafler, Brian P ^c,d   Bennett, David A ^f   Kellis, Manolis ^b,c   Tsai, Li Huei ^a,c  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^b MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^c BROAD INSTITUTE OF MIT AND HARVARD   (United States)

^d HARVARD MEDICAL SCHOOL   (United States)

^e THIRD ROCK VENTURES   (United States)

^f RUSH UNIVERSITY MEDICAL CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALPHA 1 MICROGLOBULIN; AMYLOID BETA PROTEIN; AQUAPORIN 4; CD74 ANTIGEN; COLONY STIMULATING FACTOR RECEPTOR; GLUTAMATE DECARBOXYLASE; MYELIN BASIC PROTEIN; NEU DIFFERENTIATION FACTOR; TRANSCRIPTOME; VASCULOTROPIN RECEPTOR 1; VERSICAN; MESSENGER RNA;

BIOCHEMISTRY; BRAIN; CELL; FEMALE; GENOME; MENTAL DISORDER; MOLECULAR ANALYSIS; PHYSIOLOGICAL RESPONSE;

AGED; ALZHEIMER DISEASE; ARTICLE; BRAIN CELL; CELL STRESS; CELL SUBPOPULATION; CELL SURVIVAL; CELLS BY BODY ANATOMY; CLINICAL ARTICLE; CONTROLLED STUDY; DISEASE ASSOCIATION; DISEASE SEVERITY; FEMALE; HUMAN; HUMAN CELL; HUMAN TISSUE; INFLAMMATION; MALE; MYELINATION; NERVE CELL; OLIGODENDROGLIA; PATHOPHYSIOLOGY; PREFRONTAL CORTEX; PRIORITY JOURNAL; SEX DIFFERENCE; SINGLE CELL ANALYSIS; TRANSCRIPTION INITIATION; TRANSCRIPTOMICS; UPREGULATION; VERY ELDERLY; AGING; ANTIBODY SPECIFICITY; DISEASE EXACERBATION; GENE EXPRESSION PROFILING; GENETICS; METABOLISM; PATHOLOGY; SEQUENCE ANALYSIS; SEXUAL CHARACTERISTICS;

AGING; ALZHEIMER DISEASE; DISEASE PROGRESSION; FEMALE; GENE EXPRESSION PROFILING; HUMANS; MALE; ORGAN SPECIFICITY; PREFRONTAL CORTEX; RNA, MESSENGER; SEQUENCE ANALYSIS, RNA; SEX CHARACTERISTICS; SINGLE-CELL ANALYSIS; TRANSCRIPTOME;

EID: 85066289179     PISSN: 00280836     EISSN: 14764687     Source Type: Journal    
DOI: 10.1038/s41586-019-1329-6     Document Type: Erratum

References (57)

1. Masters, C. L. et al. Alzheimer’s disease. Nat. Rev. Dis. Primers 1, 15056 (2015).
2. Hardy, J. & Selkoe, D. J. The amyloid hypothesis of Alzheimer’s disease: progress and problems on the road to therapeutics. Science 297, 353–356 (2002).
3. Braak, H. & Braak, E. Neuropathological stageing of Alzheimer-related changes. Acta Neuropathol. 82, 239–259 (1991).
4. De Strooper, B. & Karran, E. The cellular phase of Alzheimer’s disease. Cell 164, 603–615 (2016).
5. Canter, R. G., Penney, J. & Tsai, L.-H. The road to restoring neural circuits for the treatment of Alzheimer’s disease. Nature 539, 187–196 (2016).
6. Heneka, M. T. et al. Neuroinflammation in Alzheimer’s disease. Lancet Neurol. 14, 388–405 (2015).
7. Bishop, N. A., Lu, T. & Yankner, B. A. Neural mechanisms of ageing and cognitive decline. Nature 464, 529–535 (2010).
8. Pimenova, A. A., Raj, T. & Goate, A. M. Untangling genetic risk for Alzheimer’s disease. Biol. Psychiatry 83, 300–310 (2018).
9. Fisher, D. W., Bennett, D. A. & Dong, H. Sexual dimorphism in predisposition to Alzheimer’s disease. Neurobiol. Aging 70, 308–324 (2018).
10. Nativio, R. et al. Dysregulation of the epigenetic landscape of normal aging in Alzheimer’s disease. Nat. Neurosci. 21, 497–505 (2018).
11. Bossers, K. et al. Concerted changes in transcripts in the prefrontal cortex precede neuropathology in Alzheimer’s disease. Brain 133, 3699–3723 (2010).
12. Zhang, B. et al. Integrated systems approach identifies genetic nodes and networks in late-onset Alzheimer’s disease. Cell 153, 707–720 (2013).
13. Miller, J. A., Woltjer, R. L., Goodenbour, J. M., Horvath, S. & Geschwind, D. H. Genes and pathways underlying regional and cell type changes in Alzheimer’s disease. Genome Med. 5, 48 (2013).
14. Gjoneska, E. et al. Conserved epigenomic signals in mice and humans reveal immune basis of Alzheimer’s disease. Nature 518, 365–369 (2015).
15. Habib, N. et al. Massively parallel single-nucleus RNA-seq with DroNc-seq. Nat. Methods 14, 955–958 (2017).
16. Lake, B. B. et al. Neuronal subtypes and diversity revealed by single-nucleus RNA sequencing of the human brain. Science 352, 1586–1590 (2016).
17. Zhong, S. et al. A single-cell RNA-seq survey of the developmental landscape of the human prefrontal cortex. Nature 555, 524–528 (2018).
18. Lake, B. B. et al. Integrative single-cell analysis of transcriptional and epigenetic states in the human adult brain. Nat. Biotechnol. 36, 70–80 (2018).
19. Macosko, E. Z. et al. Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell 161, 1202–1214 (2015).
20. Bennett, D. A. et al. Religious Orders Study and Rush Memory and Aging Project. J. Alzheimers Dis. 64, S161–S189 (2018).
21. He, Z. et al. Comprehensive transcriptome analysis of neocortical layers in humans, chimpanzees and macaques. Nat. Neurosci. 20, 886–895 (2017).
22. Lin, Y.-T. et al. APOE4 causes widespread molecular and cellular alterations associated with Alzheimer’s disease phenotypes in human iPSC-derived brain cell types. Neuron 98, 1141–1154 (2018).
23. Mathys, H. et al. Temporal tracking of microglia activation in neurodegeneration at single-cell resolution. Cell Reports 21, 366–380 (2017).
24. Krasemann, S. et al. The TREM2–APOE pathway drives the transcriptional phenotype of dysfunctional microglia in neurodegenerative diseases. Immunity 47, 566–581 (2017).
25. Keren-Shaul, H. et al. A unique microglia type associated with restricting development of Alzheimer’s disease. Cell 169, 1276–1290 (2017).
26. Fernandez-Enright, F. & Andrews, J. L. Lingo-1: a novel target in therapy for Alzheimer’s disease? Neural Regen. Res. 11, 88–89 (2016).
27. Mi, S. et al. LINGO-1 negatively regulates myelination by oligodendrocytes. Nat. Neurosci. 8, 745–751 (2005).
28. Liang, C. et al. Erbin is required for myelination in regenerated axons after injury. J. Neurosci. 32, 15169–15180 (2012).
29. Scott, R. et al. Loss of Cntnap2 causes axonal excitability deficits, developmental delay in cortical myelination, and abnormal stereotyped motor behavior. Cereb. Cortex 29, 586–597 (2019).
30. Poplawski, G. H. D. et al. Adult rat myelin enhances axonal outgrowth from neural stem cells. Sci. Transl. Med. 10, eaal2563 (2018).
31. Khazaei, M. R. et al. Bex1 is involved in the regeneration of axons after injury. J. Neurochem. 115, 910–920 (2010).
32. Seiradake, E. et al. Structural basis for cell surface patterning through NetrinG–NGL interactions. EMBO J. 30, 4479–4488 (2011).
33. Holtzman, D. M., Morris, J. C. & Goate, A. M. Alzheimer’s disease: the challenge of the second century. Sci. Transl. Med. 3, 77sr1 (2011).
34. Andrade, W. A. et al. Early endosome localization and activity of RasGEF1b, a toll-like receptor-inducible Ras guanine-nucleotide exchange factor. Genes Immun. 11, 447–457 (2010).
35. Balch, W. E., Morimoto, R. I., Dillin, A. & Kelly, J. W. Adapting proteostasis for disease intervention. Science 319, 916–919 (2008).
36. Labbadia, J. & Morimoto, R. I. The biology of proteostasis in aging and disease. Annu. Rev. Biochem. 84, 435–464 (2015).
37. Kohonen, T. The self-organizing map. Proc. IEEE 78, 1464–1480 (1990).
38. Karch, C. M. & Goate, A. M. Alzheimer’s disease risk genes and mechanisms of disease pathogenesis. Biol. Psychiatry 77, 43–51 (2015).
39. Davies, G. et al. Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function. Nat. Commun. 9, 2098 (2018).
40. Blondel, V. D., Guillaume, J.-L., Lambiotte, R. & Lefebvre, E. Fast unfolding of communities in large networks. J. Stat. Mech. 2008, P10008 (2008).
41. Ousman, S. S. et al. Protective and therapeutic role for αB-crystallin in autoimmune demyelination. Nature 448, 474–479 (2007).
42. Shin, Y.-J. et al. Clusterin enhances proliferation of primary astrocytes through extracellular signal-regulated kinase activation. Neuroreport 17, 1871–1875 (2006).
43. Olah, M. et al. A transcriptomic atlas of aged human microglia. Nat. Commun. 9, 539 (2018).
44. Caso, F. et al. White matter degeneration in atypical Alzheimer disease. Radiology 277, 162–172 (2015).
45. Ciryam, P. et al. A transcriptional signature of Alzheimer’s disease is associated with a metastable subproteome at risk for aggregation. Proc. Natl Acad. Sci. USA 113, 4753–4758 (2016).
46. Bennett, D. A. et al. Natural history of mild cognitive impairment in older persons. Neurology 59, 198–205 (2002).
47. Bennett, D. A. et al. Apolipoprotein E ε4 allele, AD pathology, and the clinical expression of Alzheimer’s disease. Neurology 60, 246–252 (2003).
48. Bennett, D. A., Schneider, J. A., Wilson, R. S., Bienias, J. L. & Arnold, S. E. Neurofibrillary tangles mediate the association of amyloid load with clinical Alzheimer disease and level of cognitive function. Arch. Neurol. 61, 378–384 (2004).
49. Bennett, D. A. et al. Neuropathology of older persons without cognitive impairment from two community-based studies. Neurology 66, 1837–1844 (2006).
50. Bennett, D. A. et al. Decision rules guiding the clinical diagnosis of Alzheimer’s disease in two community-based cohort studies compared to standard practice in a clinic-based cohort study. Neuroepidemiology 27, 169–176 (2006).
51. Swiech, L. et al. In vivo interrogation of gene function in the mammalian brain using CRISPR–Cas9. Nat. Biotechnol. 33, 102–106 (2015).
52. Wolf, F. A., Angerer, P. & Theis, F. J. SCANPY: large-scale single-cell gene expression data analysis. Genome Biol. 19, 15 (2018).
53. Ritchie, M. E. et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 43, e47 (2015).
54. Wehrens, R. & Buydens, L. M. C. Self- and super-organizing maps in R: the kohonen package. J. Stat. Softw. 21, 1–19 (2007).
55. Zhou, Y. et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat. Commun. 10, 1523 (2019).
56. Friston, K. J. et al. Spatial registration and normalization of images. Hum. Brain Mapp. 3, 165–189 (1995).
57. Griffanti, L. et al. BIANCA (Brain Intensity AbNormality Classification Algorithm): a new tool for automated segmentation of white matter hyperintensities. Neuroimage 141, 191–205 (2016).