1. Wardlaw, J. M. et al. Neuroimaging standards for research into small vessel disease and its contribution to ageing and neurodegeneration. Lancet Neurol. 12, 822–838 (2013).

2. Kapasi, A., DeCarli, C. & Schneider, J. A. Impact of multiple pathologies on the threshold for clinically overt dementia. Acta Neuropathol. 134, 171–186 (2017).

3. Iadecola, C. The neurovascular unit coming of age: a journey through neurovascular coupling in health and disease. Neuron 96, 17–42 (2017).

4. Iturria-Medina, Y., Sotero, R. C., Toussaint, P. J., Mateos-Pérez, J. M. & Evans, A. C. Early role of vascular dysregulation on late-onset Alzheimer’s disease based on multifactorial data-driven analysis. Nat. Commun. 7, 11934 (2016).

5. Sweeney, M. D., Sagare, A. P. & Zlokovic, B. V. Blood–brain barrier breakdown in Alzheimer disease and other neurodegenerative disorders. Nat. Rev. Neurol. 14, 133–150 (2018).

6. Sweeney, M. D. et al. Vascular dysfunction—the disregarded partner of Alzheimer’s disease. Alzheimers Dement. 15, 158–167 (2019).

7. Nation, D. A. et al. Blood–brain barrier breakdown is an early biomarker of human cognitive dysfunction. Nat. Med. 25, 270–276 (2019).

8. Montagne, A. et al. Blood–brain barrier breakdown in the aging human hippocampus. Neuron 85, 296–302 (2015).

9. van de Haar, H. J. et al. Neurovascular unit impairment in early Alzheimer’s disease measured with magnetic resonance imaging. Neurobiol. Aging 45, 190–196 (2016).

10. van de Haar, H. J. et al. Blood–brain barrier leakage in patients with early Alzheimer disease. Radiology 281, 527–535 (2016).

11. Corder, E. H. et al. Gene dose of apolipoprotein E type 4 allele and the risk of Alzheimer’s disease in late onset families. Science 261, 921–923 (1993).

12. Roses, A. D. Apolipoprotein E alleles as risk factors in Alzheimer’s disease. Annu. Rev. Med. 47, 387–400 (1996).

13. Farrer, L. A. et al. Effects of age, sex, and ethnicity on the association between apolipoprotein E genotype and Alzheimer disease. A meta-analysis. J. Am. Med. Assoc. 278, 1349–1356 (1997).

14. Genin, E. et al. APOE and Alzheimer disease: a major gene with semi-dominant inheritance. Mol. Psychiatry 16, 903–907 (2011).

15. Hultman, K., Strickland, S. & Norris, E. H. The APOE ɛ4/ɛ4 genotype potentiates vascular fibrin(ogen) deposition in amyloid-laden vessels in the brains of Alzheimer’s disease patients. J. Cereb. Blood Flow Metab. 33, 1251–1258 (2013).

16. Halliday, M. R. et al. Accelerated pericyte degeneration and blood–brain barrier breakdown in apolipoprotein E4 carriers with Alzheimer’s disease. J. Cereb. Blood Flow Metab. 36, 216–227 (2016).

17. Salloway, S. et al. Effect of APOE genotype on microvascular basement membrane in Alzheimer’s disease. J. Neurol. Sci. 203-204, 183–187 (2002).

18. Zipser, B. D. et al. Microvascular injury and blood–brain barrier leakage in Alzheimer’s disease. Neurobiol. Aging 28, 977–986 (2007).

19. Bell, R. D. et al. Apolipoprotein E controls cerebrovascular integrity via cyclophilin A. Nature 485, 512–516 (2012).

20. Armulik, A. et al. Pericytes regulate the blood–brain barrier. Nature 468, 557–561 (2010).

21. Bell, R. D. et al. Pericytes control key neurovascular functions and neuronal phenotype in the adult brain and during brain aging. Neuron 68, 409–427 (2010).

22. Nikolakopoulou, A. M. et al. Pericyte loss leads to circulatory failure and pleiotrophin depletion causing neuron loss. Nat. Neurosci. 22, 1089–1098 (2019).

23. Jack, C. R. Jr et al. NIA-AA Research Framework: toward a biological definition of Alzheimer’s disease. Alzheimers Dement. 14, 535–562 (2018).

24. Pan, C. et al. Diagnostic values of cerebrospinal fluid T-Tau and Aβ 42 using meso scale discovery assays for Alzheimer’s disease. J. Alzheimers Dis. 45, 709–719 (2015).

25. Roe, C. M. et al. Amyloid imaging and CSF biomarkers in predicting cognitive impairment up to 7.5 years later. Neurology 80, 1784–1791 (2013).

26. Montagne, A., Zhao, Z. & Zlokovic, B. V. Alzheimer’s disease: a matter of blood-brain barrier dysfunction? J. Exp. Med. 214, 3151–3169 (2017).

27. Bennett, R. E. et al. Tau induces blood vessel abnormalities and angiogenesis-related gene expression in P301L transgenic mice and human Alzheimer’s disease. Proc. Natl Acad. Sci. USA 115, E1289–E1298 (2018).

28. Fouquet, M., Besson, F. L., Gonneaud, J., La Joie, R. & Chételat, G. Imaging brain effects of APOE4 in cognitively normal individuals across the lifespan. Neuropsychol. Rev. 24, 290–299 (2014).

29. Schultz, S. A. et al. Widespread distribution of tauopathy in preclinical Alzheimer’s disease. Neurobiol. Aging 72, 177–185 (2018).

30. Miners, J. S., Kehoe, P. G., Love, S., Zetterberg, H. & Blennow, K. CSF evidence of pericyte damage in Alzheimer’s disease is associated with markers of blood–brain barrier dysfunction and disease pathology. Alzheimers Res. Ther. 11, 81 (2019).

31. Stanciu, C., Trifan, A., Muzica, C. & Sfarti, C. Efficacy and safety of alisporivir for the treatment of hepatitis C infection. Expert Opin. Pharmacother. 20, 379–384 (2019).

32. Morris, J. C. et al. The Uniform Data Set (UDS): clinical and cognitive variables and descriptive data from Alzheimer Disease Centers. Alzheimer Dis. Assoc. Disord. 20, 210–216 (2006).

33. Morris, J. C. The Clinical Dementia Rating (CDR): current version and scoring rules. Neurology 43, 2412–2414 (1993).

34. Nation, D. A. et al. Antemortem pulse pressure elevation predicts cerebrovascular disease in autopsy-confirmed Alzheimer’s disease. J. Alzheimers Dis. 30, 595–603 (2012).

35. Bangen, K. J. et al. Aggregate effects of vascular risk factors on cerebrovascular changes in autopsy-confirmed Alzheimer’s disease. Alzheimers Dement. 11, 394–403.e1 (2015).

36. Jak, A. J. et al. Quantification of five neuropsychological approaches to defining mild cognitive impairment. Am. J. Geriatr. Psychiatry 17, 368–375 (2009).

37. Jak, A. J. et al. Neuropsychological criteria for mild cognitive impairment and dementia risk in the Framingham heart study. J. Int. Neuropsychol. Soc. 22, 937–943 (2016).

38. Weintraub, S. et al. The Alzheimer’s Disease Centers’ Uniform Data Set (UDS): the neuropsychologic test battery. Alzheimer Dis. Assoc. Disord. 23, 91–101 (2009).

39. Besser, L. et al. Version 3 of the National Alzheimer’s Coordinating Center’s Uniform Data Set. Alzheimer Dis. Assoc. Disord. 32, 351–358 (2018).

40. Delis, D., Kramer, J., Kaplan, E. & Ober, B. California Verbal Learning Test (PsychCorp, 2000).

41. Montagne, A. et al. Undetectable gadolinium brain retention in individuals with an age-dependent blood-brain barrier breakdown in the hippocampus and mild cognitive impairment. Alzheimers Dement. 15, 1568–1575 (2019).

42. Fischl, B. FreeSurfer. Neuroimage 62, 774–781 (2012).

43. Fischl, B. et al. Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain. Neuron 33, 341–355 (2002).

44. Desikan, R. S. et al. An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage 31, 968–980 (2006).

45. Fischl, B. & Dale, A. M. Measuring the thickness of the human cerebral cortex from magnetic resonance images. Proc. Natl Acad. Sci. USA 97, 11050–11055 (2000).

46. Fischl, B., Sereno, M. I., Tootell, R. B. & Dale, A. M. High-resolution intersubject averaging and a coordinate system for the cortical surface. Hum. Brain Mapp. 8, 272–284 (1999).

47. Dinov, I. et al. Neuroimaging study designs, computational analyses and data provenance using the LONI pipeline. PLoS ONE 5, e13070 (2010).

48. Sepehrband, F. et al. Neuroanatomical morphometric characterization of sex differences in youth using statistical learning. Neuroimage 172, 217–227 (2018).

49. Cabeen, R. P., Laidlaw, D. H. & Toga, A. W. Quantitative imaging toolkit: software for interactive 3D visualization, data exploration, and computational analysis of neuroimaging datasets. Proc. Intl Soc. Magnetic Resonance in Medicine (ISMRM) vol. 2854 (2018).

50. Jenkinson, M., Bannister, P., Brady, M. & Smith, S. Improved optimization for the robust and accurate linear registration and motion correction of brain images. Neuroimage 17, 825–841 (2002).

51. Bullich, S. et al. Optimal reference region to measure longitudinal amyloid-β change with 18F-florbetaben PET. J. Nucl. Med. 58, 1300–1306 (2017).

52. Marquié, M. et al. Lessons learned about [F-18]-AV-1451 off-target binding from an autopsy-confirmed Parkinson’s case. Acta Neuropathol. Commun. 5, 75 (2017).

53. Mishra, S. et al. AV-1451 PET imaging of tau pathology in preclinical Alzheimer disease: defining a summary measure. Neuroimage 161, 171–178 (2017).

54. TCW, J. et al. Cholesterol and matrisome pathways dysregulated in human ε4 glia. Preprint at https://www.biorxiv.org/content/10.1101/713362v1 (2019).

55. Faal, T. et al. Induction of mesoderm and neural crest-derived pericytes from human pluripotent stem cells to study blood-brain barrier interactions. Stem Cell Reports 12, 451–460 (2019).

56. Aggarwal, C. C. Outlier Analysis (Springer, 2013).

57. Sagare, A. P., Sweeney, M. D., Makshanoff, J. & Zlokovic, B. V. Shedding of soluble platelet-derived growth factor receptor-β from human brain pericytes. Neurosci. Lett. 607, 97–101 (2015).