Skip to main content

Advertisement

Log in

Clinical Research on Alzheimer’s Disease: Progress and Perspectives

  • Review
  • Published:
Neuroscience Bulletin Aims and scope Submit manuscript

Abstract

Alzheimer’s disease (AD), the most common type of dementia, is becoming a major challenge for global health and social care. However, the current understanding of AD pathogenesis is limited, and no early diagnosis and disease-modifying therapy are currently available. During the past year, significant progress has been made in clinical research on the diagnosis, prevention, and treatment of AD. In this review, we summarize the latest achievements, including diagnostic biomarkers, polygenic hazard score, amyloid and tau PET imaging, clinical trials targeting amyloid-beta (Aβ), tau, and neurotransmitters, early intervention, and primary prevention and systemic intervention approaches, and provide novel perspectives for further efforts to understand and cure the disease.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

(Figures adapted from Nakamura et al. [15] with permission)

Fig. 2

(Image adapted from Desikan et al. [24] with permission)

Fig. 3

(Image adapted from Livingston et al. [2] with permission)

Similar content being viewed by others

References

  1. Dubois B, Feldman HH, Jacova C, Hampel H, Molinuevo JL, Blennow K, et al. Advancing research diagnostic criteria for Alzheimer’s disease: the IWG-2 criteria. Lancet Neurol 2014, 13: 614–629.

    Article  Google Scholar 

  2. Livingston G, Sommerlad A, Orgeta V, Costafreda SG, Huntley J, Ames D, et al. Dementia prevention, intervention, and care. Lancet 2017, 390: 2673–2734.

    Article  Google Scholar 

  3. Wang QH, Wang X, Bu XL, Lian Y, Xiang Y, Luo HB, et al. Comorbidity burden of dementia: a hospital-based retrospective study from 2003 to 2012 in seven cities in China. Neurosci Bull 2017, 33: 703–710.

    Article  Google Scholar 

  4. Li C, Gotz J. Tau-based therapies in neurodegeneration: opportunities and challenges. Nat Rev Drug Discov 2017, 16: 863–883.

    Article  CAS  Google Scholar 

  5. Chetelat G. Multimodal neuroimaging in Alzheimer’s disease: early diagnosis, physiopathological mechanisms, and impact of lifestyle. J Alzheimers Dis 2018. https://doi.org/10.3233/jad-179920.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Misra MK, Damotte V, Hollenbach JA. The immunogenetics of neurological disease. Immunology 2018, 153: 399–414.

    CAS  PubMed  Google Scholar 

  7. Frisoni GB, Boccardi M, Barkhof F, Blennow K, Cappa S, Chiotis K, et al. Strategic roadmap for an early diagnosis of Alzheimer’s disease based on biomarkers. Lancet Neurol 2017, 16: 661–676.

    Article  Google Scholar 

  8. O’Bryant SE, Mielke MM, Rissman RA, Lista S, Vanderstichele H, Zetterberg H, et al. Blood-based biomarkers in Alzheimer disease: current state of the science and a novel collaborative paradigm for advancing from discovery to clinic. Alzheimers Dement 2017, 13: 45–58.

    Article  Google Scholar 

  9. Snyder HM, Carrillo MC, Grodstein F, Henriksen K, Jeromin A, Lovestone S, et al. Developing novel blood-based biomarkers for Alzheimer’s disease. Alzheimers Dement 2014, 10: 109–114.

    Article  Google Scholar 

  10. Kim HJ, Park KW, Kim TE, Im JY, Shin HS, Kim S, et al. Elevation of the plasma Abeta40/Abeta42 ratio as a diagnostic marker of sporadic early-onset Alzheimer’s disease. J Alzheimers Dis 2015, 48: 1043–1050.

    Article  CAS  Google Scholar 

  11. Koyama A, Okereke OI, Yang T, Blacker D, Selkoe DJ, Grodstein F. Plasma amyloid-beta as a predictor of dementia and cognitive decline: a systematic review and meta-analysis. Arch Neurol 2012, 69: 824–831.

    Article  Google Scholar 

  12. Petersen RC, Aisen PS, Beckett LA, Donohue MC, Gamst AC, Harvey DJ, et al. Alzheimer’s Disease Neuroimaging Initiative (ADNI): clinical characterization. Neurology 2010, 74: 201–209.

    Article  Google Scholar 

  13. Fandos N, Perez-Grijalba V, Pesini P, Olmos S, Bossa M, Villemagne VL, et al. Plasma amyloid beta 42/40 ratios as biomarkers for amyloid beta cerebral deposition in cognitively normal individuals. Alzheimers Dement (Amst) 2017, 8: 179–187.

    Google Scholar 

  14. Ovod V, Ramsey KN, Mawuenyega KG, Bollinger JG, Hicks T, Schneider T, et al. Amyloid beta concentrations and stable isotope labeling kinetics of human plasma specific to central nervous system amyloidosis. Alzheimers Dement 2017, 13: 841–849.

    Article  Google Scholar 

  15. Nakamura A, Kaneko N, Villemagne VL, Kato T, Doecke J, Doré V, et al. High performance plasma amyloid-β biomarkers for Alzheimer’s disease. Nature 2018, 554: 249–254.

    Article  CAS  Google Scholar 

  16. Buckley RF, Hanseeuw B, Schultz AP, Vannini P, Aghjayan SL, Properzi MJ, et al. Region-specific association of subjective cognitive decline with tauopathy independent of global beta-amyloid burden. JAMA Neurol 2017, 74: 1455–1463.

    Article  Google Scholar 

  17. Varma VR, Oommen AM, Varma S, Casanova R, An Y, Andrews RM, et al. Brain and blood metabolite signatures of pathology and progression in Alzheimer disease: a targeted metabolomics study. PLoS Med 2018, 15: e1002482.

    Article  Google Scholar 

  18. Sagare A, Deane R, Bell RD, Johnson B, Hamm K, Pendu R, et al. Clearance of amyloid-beta by circulating lipoprotein receptors. Nat Med 2007, 13: 1029–1031.

    Article  CAS  Google Scholar 

  19. Mortberg E, Zetterberg H, Nordmark J, Blennow K, Catry C, Decraemer H, et al. Plasma tau protein in comatose patients after cardiac arrest treated with therapeutic hypothermia. Acta Anaesthesiol Scand 2011, 55: 1132–1138.

    Article  CAS  Google Scholar 

  20. Yang SY, Chiu MJ, Chen TF, Horng HE. Detection of plasma biomarkers using immunomagnetic reduction: a promising method for the early diagnosis of Alzheimer’s disease. Neurol Ther 2017, 6: 37–56.

    Article  Google Scholar 

  21. Lue LF, Sabbagh MN, Chiu MJ, Jing N, Snyder NL, Schmitz C, et al. Plasma levels of Abeta42 and Tau identified probable Alzheimer’s dementia: findings in two cohorts. Front Aging Neurosci 2017, 9: 226.

    Article  Google Scholar 

  22. Mattsson N, Andreasson U, Zetterberg H, Blennow K. Alzheimer’s disease neuroimaging initiative. Association of plasma neurofilament light with neurodegeneration in patients with Alzheimer disease. JAMA Neurol 2017, 74: 557–566.

    Article  Google Scholar 

  23. Zetterberg H, Skillback T, Mattsson N, Trojanowski JQ, Portelius E, Shaw LM, et al. Association of cerebrospinal fluid neurofilament light concentration With Alzheimer disease progression. JAMA Neurol 2016, 73: 60–67.

    Article  Google Scholar 

  24. Desikan RS, Fan CC, Wang Y, Schork AJ, Cabral HJ, Cupples LA, et al. Genetic assessment of age-associated Alzheimer disease risk: development and validation of a polygenic hazard score. PLoS Med 2017, 14: e1002258.

    Article  Google Scholar 

  25. Tan CH, Fan CC, Mormino EC, Sugrue LP, Broce IJ, Hess CP, et al. Polygenic hazard score: an enrichment marker for Alzheimer’s associated amyloid and tau deposition. Acta Neuropathol 2018, 135: 85–93.

    Article  CAS  Google Scholar 

  26. Sepulcre J, Grothe MJ, Sabuncu M, Chhatwal J, Schultz AP, Hanseeuw B, et al. Hierarchical organization of Tau and amyloid deposits in the cerebral cortex. JAMA Neurol 2017, 74: 813–820.

    Article  Google Scholar 

  27. Selkoe DJ, Hardy J. The amyloid hypothesis of Alzheimer’s disease at 25 years. EMBO Mol Med 2016, 8: 595–608.

    Article  CAS  Google Scholar 

  28. Wang J, Gu BJ, Masters CL, Wang YJ. A systemic view of Alzheimer disease—insights from amyloid-beta metabolism beyond the brain. Nat Rev Neurol 2017, 13: 612–623.

    Article  CAS  Google Scholar 

  29. Kennedy ME, Stamford AW, Chen X, Cox K, Cumming JN, Dockendorf MF, et al. The BACE1 inhibitor verubecestat (MK-8931) reduces CNS β-amyloid in animal models and in Alzheimer’s disease patients. Sci Transl Med 2016, 8(363): 363ra150.

    Article  Google Scholar 

  30. Maher-Edwards G, Dixon R, Hunter J, Gold M, Hopton G, Jacobs G, et al. SB-742457 and donepezil in Alzheimer disease: a randomized, placebo-controlled study. Int J Geriatr Psychiatry 2011, 26: 536–544.

    Article  Google Scholar 

  31. Siemers ER, Sundell KL, Carlson C, Case M, Sethuraman G, Liu-Seifert H, et al. Phase 3 solanezumab trials: secondary outcomes in mild Alzheimer’s disease patients. Alzheimers Dement 2016, 12: 110–120.

    Article  Google Scholar 

  32. Honig LS, Vellas B, Woodward M, Boada M, Bullock R, Borrie M, et al. Trial of Solanezumab for mild dementia due to Alzheimer’s disease. N Engl J Med 2018, 378: 321–330.

    Article  CAS  Google Scholar 

  33. Sevigny J, Chiao P, Bussiere T, Weinreb PH, Williams L, Maier M, et al. The antibody aducanumab reduces Abeta plaques in Alzheimer’s disease. Nature 2016, 537: 50–56.

    Article  CAS  Google Scholar 

  34. Adolfsson O, Pihlgren M, Toni N, Varisco Y, Buccarello AL, Antoniello K, et al. An effector-reduced anti-beta-amyloid (Abeta) antibody with unique abeta binding properties promotes neuroprotection and glial engulfment of Abeta. J Neurosci 2012, 32: 9677–9689.

    Article  CAS  Google Scholar 

  35. Ostrowitzki S, Deptula D, Thurfjell L, Barkhof F, Bohrmann B, Brooks DJ, et al. Mechanism of amyloid removal in patients with Alzheimer disease treated with gantenerumab. Arch Neurol 2012, 69: 198–207.

    Article  Google Scholar 

  36. Liu YH, Giunta B, Zhou HD, Tan J, Wang YJ. Immunotherapy for Alzheimer disease: the challenge of adverse effects. Nat Rev Neurol 2012, 8: 465–469.

    Article  CAS  Google Scholar 

  37. Busche MA, Grienberger C, Keskin AD, Song B, Neumann U, Staufenbiel M, et al. Decreased amyloid-beta and increased neuronal hyperactivity by immunotherapy in Alzheimer’s models. Nat Neurosci 2015, 18: 1725–1727.

    Article  CAS  Google Scholar 

  38. Jack CR, Knopman DS, Jagust WJ, Petersen RC, Weiner MW, Aisen PS, et al. Tracking pathophysiological processes in Alzheimer’s disease: an updated hypothetical model of dynamic biomarkers. Lancet Neurol 2013, 12: 207–216.

    Article  CAS  Google Scholar 

  39. Wischik CM, Staff RT, Wischik DJ, Bentham P, Murray AD, Storey JM, et al. Tau aggregation inhibitor therapy: an exploratory phase 2 study in mild or moderate Alzheimer’s disease. J Alzheimers Dis 2015, 44: 705–720.

    Article  CAS  Google Scholar 

  40. Mullard A. Pharma pumps up anti-tau Alzheimer pipeline despite first phase III failure. Nat Rev Drug Discov 2016, 15: 591–592.

    Article  CAS  Google Scholar 

  41. Wilcock GK, Gauthier S, Frisoni GB, Jia J, Hardlund JH, Moebius HJ, et al. Potential of low dose leuco-methylthioninium bis(hydromethanesulphonate) (LMTM) monotherapy for treatment of mild Alzheimer’s disease: cohort analysis as modified primary outcome in a phase III clinical trial. J Alzheimers Dis 2018, 61: 435–457.

    Article  CAS  Google Scholar 

  42. Novak P, Schmidt R, Kontsekova E, Zilka N, Kovacech B, Skrabana R, et al. Safety and immunogenicity of the tau vaccine AADvac1 in patients with Alzheimer’s disease: a randomised, double-blind, placebo-controlled, phase 1 trial. Lancet Neurol 2017, 16: 123–134.

    Article  CAS  Google Scholar 

  43. West T, Hu Y, Verghese PB, Bateman RJ, Braunstein JB, Fogelman I, et al. Preclinical and clinical development of ABBV-8E12, a humanized anti-Tau antibody, for treatment of Alzheimer’s disease and other tauopathies. J Prev Alzheimers Dis 2017, 4: 236–241.

    CAS  PubMed  Google Scholar 

  44. Bateman RJ, Xiong C, Benzinger TL, Fagan AM, Goate A, Fox NC, et al. Clinical and biomarker changes in dominantly inherited Alzheimer’s disease. N Engl J Med 2012, 367: 795–804.

    Article  CAS  Google Scholar 

  45. Villeda SA, Plambeck KE, Middeldorp J, Castellano JM, Mosher KI, Luo J, et al. Young blood reverses age-related impairments in cognitive function and synaptic plasticity in mice. Nat Med 2014, 20: 659–663.

    Article  CAS  Google Scholar 

  46. Middeldorp J, Lehallier B, Villeda SA, Miedema SS, Evans E, Czirr E, et al. Preclinical assessment of young blood plasma for Alzheimer disease. JAMA Neurol 2016, 73: 1325–1333.

    Article  Google Scholar 

  47. Xiang Y, Bu XL, Liu YH, Zhu C, Shen LL, Jiao SS, et al. Physiological amyloid-beta clearance in the periphery and its therapeutic potential for Alzheimer’s disease. Acta Neuropathol 2015, 130: 487–499.

    Article  CAS  Google Scholar 

  48. Castellano JM, Mosher KI, Abbey RJ, McBride AA, James ML, Berdnik D, et al. Human umbilical cord plasma proteins revitalize hippocampal function in aged mice. Nature 2017, 544: 488–492.

    Article  CAS  Google Scholar 

  49. Bu XL, Xiang Y, Jin WS, Wang J, Shen LL, Huang ZL, et al. Blood-derived amyloid-beta protein induces Alzheimer’s disease pathologies. Mol Psychiatry 2017. https://doi.org/10.1038/mp.2017.204.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Jin WS, Shen LL, Bu XL, Zhang WW, Chen SH, Huang ZL, et al. Peritoneal dialysis reduces amyloid-beta plasma levels in humans and attenuates Alzheimer-associated phenotypes in an APP/PS1 mouse model. Acta Neuropathol 2017, 134: 207–220.

    Article  CAS  Google Scholar 

  51. Pan X, Chen Z, Fei G, Pan S, Bao W, Ren S, et al. Long-term cognitive improvement after benfotiamine administration in patients with Alzheimer’s disease. Neurosci Bull 2016, 32: 591–596.

    Article  CAS  Google Scholar 

Download references

Acknowledgements

This review was supported by the the Chinese Ministry of Science and Technology (2016YFC1306401).

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Xiu-Qing Yao or Yan-Jiang Wang.

Ethics declarations

Conflict of interest

All authors claim that there are no conflicts of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sun, BL., Li, WW., Zhu, C. et al. Clinical Research on Alzheimer’s Disease: Progress and Perspectives. Neurosci. Bull. 34, 1111–1118 (2018). https://doi.org/10.1007/s12264-018-0249-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12264-018-0249-z

Keywords

Navigation