Artificial Intelligence and Alzheimer’s Disease: Bridging Complexity with Precision Medicine
DOI:
https://doi.org/10.53555/jaz.v45i5.5206Keywords:
Alzheimer’s Disease, Artificial Intelligence, Dementia, Clinical MedicineAbstract
The most prevalent cause of dementia and a progressive neurodegenerative illness, Alzheimer's disease (AD) has a substantial negative impact on both global health and the economy. There is presently no cure, despite much study, and treatments like memantine and cholinesterase inhibitors just alleviate symptoms. The multifaceted character of AD, comprising intricate genetic, epigenetic, and environmental connections, has been brought to light by developments in genomics, neuroimaging, and clinical data. Novel computational techniques are necessary since traditional methods often fail to understand such high-dimensional information. In AD research, artificial intelligence (AI), especially machine learning and deep learning, has become a game-changing tool. In order to enable early diagnosis, prognosis, biomarker identification, and therapy development, artificial intelligence (AI) makes it easier to analyze large datasets from next-generation sequencing (NGS), transcriptomics, proteomics, imaging, and genome-wide association studies (GWAS). AI applications in AD include determining transcriptomic and epigenetic biomarkers, discovering new gene-gene interactions, connecting neuroimaging indicators with genetic differences, and predicting disease risk using genetic risk scores. Furthermore, by combining multifaceted biological and clinical data, AI-driven methods facilitate drug discovery, repurposing, and clinical trial optimization. Recent research highlights AI's promise in precision medicine for AD by showing that it can combine genetic, imaging, and biomarker data to reach high prediction accuracy. Nonetheless, there are still issues with clinical validation, data heterogeneity, and interpretability. The uses of AI in deciphering the genetics and pathophysiology of AD are highlighted in this study, along with current advancements and constraints. It also offers insights into potential future paths where AI might speed up the conversion of complicated data into useful methods for AD diagnosis and therapy.
Downloads
References
1. Chen X, Zhang X, Li X, Zhao Y, Yang L, Wang Y, et al. Recent advances in the diagnosis and treatment of Alzheimer’s disease. Front Genet. 2023;14:1138270.
2. Jeong S. Molecular and cellular basis of neurodegeneration in Alzheimer’s disease. Mol Cells. 2017;40(9):613–20.
3. Mudher A, Lovestone S. Alzheimer’s disease—do tauists and baptists finally shake hands? Trends Neurosci. 2002;25(1):22–6.
4. Liu YH, Giunta B, Zhou HD, Tan J, Wang YJ. Immunotherapy for Alzheimer’s disease. Biomed Pharmacother. 2011;65(7):539–46.
5. Pujari R, Vyawahare N. Alzheimer’s disease: future drug development strategies. Int J Pharm Sci Rev Res. 2014;29(2):138–47.
6. Murphy MP, Levine H. Alzheimer’s disease and the amyloid-beta peptide. J Alzheimers Dis. 2010;19(1):311–23.
7. Chen C, Guo T, Wang J, Guo H, Zhang C, Zhang L, et al. Research progress of Alzheimer’s disease detection technology based on nano-biosensing. Front Aging Neurosci. 2023;15:1181815.
8. Jeong S. Molecular and cellular basis of neurodegeneration in Alzheimer’s disease. Mol Cells. 2017;40(9):613–20.
9. Karran E, Mercken M, De Strooper B. The amyloid cascade hypothesis for Alzheimer’s disease: an appraisal for the development of therapeutics. Nat Rev Drug Discov. 2011;10(9):698–712.
10. Yu W, Lu B. Synapses and dendritic spines as pathogenic targets in Alzheimer’s disease. Neural Plast. 2012;2012:247150.
11. Nasr P, Gopalkrishna S, Manoharan R, Jayaraj RL, Elangovan N. Alzheimer’s disease: A molecular view of β-amyloid induced neurodegeneration, mechanisms and prevention. Int J Neurosci. 2019;129(4):333–50.
12. Forner S, Baglietto-Vargas D, Martini AC, Trujillo-Estrada L, LaFerla FM. Synaptic impairment in Alzheimer’s disease: a dysregulated symphony. Trends Neurosci. 2017;40(6):347–57.
13. Agrawal M, Biswas A. Molecular diagnostics of neurodegenerative disorders. Front Mol Biosci. 2015;2:54.
14. Weiner MW, Veitch DP, Aisen PS, Beckett LA, Cairns NJ, Green RC, et al. The Alzheimer’s Disease Neuroimaging Initiative: a review of papers published since its inception. Alzheimers Dement. 2012;8(1 Suppl):S1–68.
15. Dugger BN, Dickson DW. Pathology of neurodegenerative diseases. Cold Spring Harb Perspect Biol. 2017;9(7):a028035.
16. Rajmohan R, Reddy PH. Amyloid-beta and phosphorylated tau accumulations cause abnormalities at synapses of Alzheimer’s disease neurons. J Alzheimers Dis. 2017;57(4):975–99.
17. Jellinger KA. Neuropathological aspects of Alzheimer disease, Parkinson disease and frontotemporal dementia. Neurodegener Dis. 2008;5(3–4):118–21.
18. Serrano-Pozo A, Frosch MP, Masliah E, Hyman BT. Neuropathological alterations in Alzheimer disease. Cold Spring Harb Perspect Med. 2011;1(1):a006189.
19. Oakley H, Cole SL, Logan S, Maus E, Shao P, Craft J, et al. Intraneuronal β-amyloid aggregates, neurodegeneration, and neuron loss in transgenic mice with five familial Alzheimer’s disease mutations: potential factors in amyloid plaque formation. J Neurosci. 2006;26(40):10129–40.
20. Iqbal K, Liu F, Gong CX, Grundke-Iqbal I. Tau in Alzheimer disease and related tauopathies. Curr Alzheimer Res. 2010;7(8):656–64.
21. Serrano-Pozo A, Frosch MP, Masliah E, Hyman BT. Neuropathological alterations in Alzheimer disease. Cold Spring Harb Perspect Med. 2011;1(1):a006189.
22. Brier MR, Gordon B, Friedrichsen K, McCarthy J, Stern A, Christensen J, et al. Tau and Aβ imaging, CSF measures, and cognition in Alzheimer’s disease. Sci Transl Med. 2016;8(338):338ra66.
23. Selkoe DJ, Hardy J. The amyloid hypothesis of Alzheimer’s disease at 25 years. EMBO Mol Med. 2016;8(6):595–608.
24. Uddin MS, Kabir MT, Rahman MS, Behl T, Jeandet P, Ashraf GM, et al. Revisiting the amyloid cascade hypothesis: From anti-Aβ therapeutics to auspicious new ways for Alzheimer’s disease. Int J Mol Sci. 2020;21(16):5858.
25. D’Argenio V, Sarnataro D. New insights into the molecular bases of familial Alzheimer’s disease. J Pers Med. 2020;10(1):26.
26. Alavi Naini SM, Soussi-Yanicostas N. Tau hyperphosphorylation and oxidative stress, a critical vicious circle in neurodegenerative tauopathies? Oxid Med Cell Longev. 2015;2015:151979.
27. Liu B, Liu J, Shi JS. SIRT1 and Alzheimer’s disease: modulation of amyloid-beta peptide generation. Neurosci Bull. 2008;24(5):439–44.
28. Lesné S, Koh MT, Kotilinek L, Kayed R, Glabe CG, Yang A, et al. A specific amyloid-beta protein assembly in the brain impairs memory. Nature. 2006;440(7082):352–7.
29. Liao D, Miller EC, Teravskis PJ. Tau acts as a mediator for Alzheimer’s disease-related synaptic deficits. Eur J Neurosci. 2014;39(7):1202–13.
30. Bloom GS. Amyloid-β and tau: the trigger and bullet in Alzheimer disease pathogenesis. JAMA Neurol. 2014;71(4):505–8.
31. Evans DA, Funkenstein HH, Albert MS, Scherr PA, Cook NR, Chown MJ, et al. Prevalence of Alzheimer’s disease in a community population of older persons. Higher than previously reported. JAMA. 1989;262(18):2551–6.
32. Green RC, Cupples LA, Go R, Benke KS, Edeki T, Griffith PA, et al. Risk of dementia among white and African American relatives of patients with Alzheimer disease. JAMA. 2002;287(3):329–36.
33. Harris JR, editor. New insights into Alzheimer’s disease. Vol. 2. Amsterdam: Elsevier; 2006.
34. Scheuner D, Eckman C, Jensen M, Song X, Citron M, Suzuki N, et al. Secreted amyloid beta-protein similar to that in the senile plaques of Alzheimer’s disease is increased in vivo by the presenilin 1 and 2 and APP mutations linked to familial Alzheimer’s disease. Nat Med. 1996;2(8):864–70.
35. Duyckaerts C, Potier MC, Delatour B. Alzheimer disease models and human neuropathology: similarities and differences. Acta Neuropathol. 2008;115(1):5–38.
36. Mayeux R, Stern Y. Epidemiology of Alzheimer disease. Cold Spring Harb Perspect Med. 2012;2(8):a006239.
37. Viña J, Lloret A, Giraldo E, Badía MC, Alonso MD. Antioxidant pathways in Alzheimer’s disease: possibilities of intervention. Curr Pharm Des. 2011;17(35):3861–4.
38. Hardy J, Selkoe DJ. The amyloid hypothesis of Alzheimer’s disease: progress and problems on the road to therapeutics. Science. 2002;297(5580):353–6.
39. Dhillon S. Aducanumab: First approval. Drugs. 2021;81(12):1437–42.
40. Tolar M, Abushakra S, Hey JA, Porsteinsson A, Sabbagh M. Aducanumab, gantenerumab, BAN2401, and ALZ-801—the first wave of amyloid-targeting drugs for Alzheimer’s disease with potential for near term approval. Alzheimers Res Ther. 2020;12(1):95.
41. Budd Haeberlein S, Aisen PS, Barkhof F, Chalkias S, Chen T, Cohen S, et al. Two randomized phase 3 studies of aducanumab in early Alzheimer’s disease. J Prev Alzheimers Dis. 2022;9(2):197–210.
42. Haeberlein SB, von Hehn C, Tian Y, Chalkias S, Muralidharan KK, Chen T, et al. Emerge and Engage topline results: Two phase 3 studies to evaluate aducanumab in patients with early Alzheimer’s disease. Alzheimers Dement. 2019;15(Suppl 7):P2734–5.
43. Lin YT, Seo J, Gao F, Feldman HM, Wen HL, Penney J, et al. APOE4 causes widespread molecular and cellular alterations associated with Alzheimer’s disease phenotypes in human iPSC-derived brain cell types. Neuron. 2018;98(6):1141–54.e7.
44. Karran E, De Strooper B. The amyloid cascade hypothesis: are we poised for success or failure? J Neurochem. 2016;139(Suppl 2):237–52.
45. Congdon EE, Sigurdsson EM. Tau-targeting therapies for Alzheimer disease. Nat Rev Neurol. 2018;14(7):399–415.
46. Long JM, Holtzman DM. Alzheimer disease: an update on pathobiology and treatment strategies. Cell. 2019;179(2):312–39.
47. Knopman DS, Amieva H, Petersen RC, Chételat G, Holtzman DM, Hyman BT, et al. Alzheimer disease. Nat Rev Dis Primers. 2021;7(1):33.
48. Peng C, Trojanowski JQ, Lee VM. Protein transmission in neurodegenerative disease. Nat Rev Neurol. 2020;16(4):199–212.
49. Nisbet RM, Polanco JC, Ittner LM, Götz J. Tau aggregation and its interplay with amyloid-β. Acta Neuropathol. 2015;129(2):207–20.
50. Robinson JL, Lee EB, Xie SX, Rennert L, Suh E, Bredenberg C, et al. Neurodegenerative disease concomitant proteinopathies are prevalent, age-related and APOE4-associated. Brain. 2018;141(7):2181–93.
51. Pascoal TA, Benedet AL, Ashton NJ, Kang MS, Therriault J, Chamoun M, et al. Microglial activation and tau propagate jointly across Braak stages. Nat Med. 2021;27(9):1592–9.
52. Henstridge CM, Hyman BT, Spires-Jones TL. Beyond the neuron–cellular interactions early in Alzheimer disease pathogenesis. Nat Rev Neurosci. 2019;20(2):94–108.
53. Hampel H, Vassar R, De Strooper B, Hardy J, Willem M, Singh N, et al. The β-secretase BACE1 in Alzheimer’s disease. Biol Psychiatry. 2021;89(8):745–56.
54. Wang Y, Cella M, Mallinson K, Ulrich JD, Young KL, Robinette ML, et al. TREM2 lipid sensing sustains the microglial response in an Alzheimer’s disease model. Cell. 2015;160(6):1061–71.
55. Ulland TK, Song WM, Huang SC, Ulrich JD, Sergushichev A, Beatty WL, et al. TREM2 maintains microglial metabolic fitness in Alzheimer’s disease. Cell. 2017;170(4):649–63.e13.
56. Ghosh AK, Osswald HL. BACE1 (β-secretase) inhibitors for the treatment of Alzheimer’s disease. Chem Soc Rev. 2014;43(19):6765–813.
57. Egan MF, Kost J, Tariot PN, Aisen PS, Cummings JL, Vellas B, et al. Randomized trial of verubecestat for prodromal Alzheimer’s disease. N Engl J Med. 9 2019;380(15):1408–20.
58. Makin S. The amyloid hypothesis on trial. Nature. 2018;559(7715):S4–7.
59. Mullard A. Alzheimer amyloid hypothesis lives on. Nat Rev Drug Discov. 2021;20(1):3–6.
60. 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(4):321–30.
61. Selkoe DJ. Alzheimer disease and aducanumab: adjusting our approach. Nat Rev Neurol. 2019;15(7):365–6.
62. Sevigny J, Chiao P, Bussière T, Weinreb PH, Williams L, Maier M, et al. The antibody aducanumab reduces Aβ plaques in Alzheimer’s disease. Nature. 2016;537(7618):50–6.
63. Ostrowitzki S, Lasser RA, Dorflinger E, Scheltens P, Barkhof F, Nikolcheva T, et al. A phase III randomized trial of gantenerumab in prodromal Alzheimer’s disease. Alzheimers Res Ther. 2017;9(1):95.
64. Panza F, Lozupone M, Logroscino G, Imbimbo BP. A critical appraisal of amyloid-β-targeting therapies for Alzheimer disease. Nat Rev Neurol. 2019;15(2):73–88.
65. 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(2):198–207.
66. Tucker S, Möller C, Tegerstedt K, Lord A, Laudon H, Sjödahl J, et al. The murine version of BAN2401 (mAb158) selectively reduces amyloid-β protofibrils in brain and cerebrospinal fluid of tg-ArcSwe mice. J Alzheimers Dis. 2015;43(2):575–88.
67. Swanson CJ, Zhang Y, Dhadda S, Wang J, Kaplow J, Lai RYK, et al. Trial of BAN2401 for early Alzheimer’s disease. N Engl J Med. 2021;385(18):1649–61.
68. Van Dyck CH, Swanson CJ, Aisen P, Bateman RJ, Chen C, Gee M, et al. Lecanemab in early Alzheimer’s disease. N Engl J Med. 2023;388(1):9–21.
69. Høilund-Carlsen PF, Frokjaer JB, Rubin P, Alavi A. Lecanemab: the need for new trials. J Alzheimers Dis. 2023;94(1):1–5.
70. Sims JR, Zimmer JA, Evans CD, Lu M, Ardayfio P, Sparks J, et al. Donanemab in early symptomatic Alzheimer disease: The TRAILBLAZER-ALZ 2 randomized clinical trial. JAMA. 2023;330(6):512–27.
71. Mintun MA, Lo AC, Duggan Evans C, Wessels AM, Ardayfio PA, Andersen SW, et al. Donanemab in early Alzheimer’s disease. N Engl J Med. 2021;384(18):1691–704.
72. Tolar M, Abushakra S, Hey JA, Porsteinsson A, Sabbagh M. Aducanumab, gantenerumab, BAN2401, and ALZ-801—the first wave of amyloid-targeting drugs for Alzheimer’s disease with potential for near term approval. Alzheimers Res Ther. 2020;12(1):95.
73. Høilund-Carlsen PF, Edenbrandt L, Alavi A. Global, regional, and national burden of Alzheimer’s disease and other dementias, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 2019;18(1):88–106.
74. Tarawneh R, Holtzman DM. The clinical problem of symptomatic Alzheimer disease and mild cognitive impairment. Cold Spring Harb Perspect Med. 2012;2(5):a006148.
75. Rabinovici GD. Controversy and progress in Alzheimer’s disease—FDA approval of aducanumab. N Engl J Med. 2021;385(9):771–4.
76. Knopman DS, Perlmutter JS. Prescribing Aduhelm in the United States—CMS proposes an answer. Nat Rev Neurol. 2022;18(3):125–6.
77. Alexander GC, Emerson S, Kesselheim AS. Evaluation of aducanumab for Alzheimer disease: scientific evidence and regulatory review involving efficacy, safety, and futility. JAMA. 2021;325(17):1717–8.
78. Høilund-Carlsen PF, Frokjaer JB, Edenbrandt L, Alavi A. The FDA approval of aducanumab for Alzheimer’s disease: The need for a paradigm shift. J Alzheimers Dis. 2022;85(2):427–30.
79. Whitehouse PJ. The end of Alzheimer’s disease—not with a bang but a whimper. J Alzheimers Dis. 2014;40(3):S141–3.
80. Panza F, Seripa D, Solfrizzi V, Imbimbo BP, Lozupone M, Santamato A, et al. Targeting amyloid-β peptide in Alzheimer’s disease: biological and pharmacological perspectives. Expert Opin Ther Targets. 2016;20(7):693–702.
81. Cummings J, Aisen PS, DuBois B, Frölich L, Jack CR, Jones RW, et al. Drug development in Alzheimer’s disease: the path to 2025. Alzheimers Res Ther. 2016;8(1):39.
82. Yiannopoulou KG, Papageorgiou SG. Current and future treatments for Alzheimer’s disease. Ther Adv Neurol Disord. 2013;6(1):19–33.
83. Reiss AB, Arain HA, Stecker MM, Siegart NM, Kasselman LJ. Amyloid toxicity in Alzheimer’s disease. Rev Neurosci. 2018;29(6):613–27.
84. 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(2):123–34.
85. Cummings JL, Morstorf T, Zhong K. Alzheimer’s disease drug-development pipeline: few candidates, frequent failures. Alzheimers Res Ther. 2014;6(4):37.
86. Schindler SE, Bollinger JG, Ovod V, Mawuenyega KG, Li Y, Gordon BA, et al. High-precision plasma β-amyloid 42/40 predicts current and future brain amyloidosis. Neurology. 2019;93(17):e1647–59. doi: 10.1212/WNL.0000000000008081.
87. Janelidze S, Mattsson N, Palmqvist S, Smith R, Beach TG, Serrano GE, et al. Plasma P-tau181 in Alzheimer’s disease: relationship to other biomarkers, differential diagnosis, neuropathology and longitudinal progression to Alzheimer’s dementia. Nat Med. 2020;26(3):379–86. doi: 10.1038/s41591-020-0755-1.
88. Palmqvist S, Tideman P, Cullen N, Zetterberg H, Blennow K, Dage JL, et al. Prediction of future Alzheimer’s disease dementia using plasma phospho-tau combined with other accessible measures. Nat Med. 2021;27(6):1034–42. doi: 10.1038/s41591-021-01348-z.
89. De Simone MS, De Tollis M, Fadda L, Perri R, Caltagirone C, Carlesimo GA. Lost or unavailable? Exploring mechanisms that affect retrograde memory in mild cognitive impairment and Alzheimer’s disease patients. J Neurol. 2020;267(1):113–24. doi: 10.1007/s00415-019-09559-8.
90. De Simone MS, Perri R, Fadda L, De Tollis M, Turchetta CS, Caltagirone C, et al. Different deficit patterns on word lists and short stories predict conversion to Alzheimer’s disease in patients with amnestic mild cognitive impairment. J Neurol. 2017;264(11):2258–67. doi: 10.1007/s00415-017-8623-8.
91. De Simone MS, Perri R, Fadda L, Caltagirone C, Carlesimo GA. Predicting progression to Alzheimer’s disease in subjects with amnestic mild cognitive impairment using performance on recall and recognition tests. J Neurol. 2019;266(1):102–11. doi: 10.1007/s00415-018-9108-0.
92. Di Lorenzo F, Motta C, Casula EP, Bonnì S, Assogna M, Caltagirone C, et al. LTP-like cortical plasticity predicts conversion to dementia in patients with memory impairment. Brain Stimul. 2020;13(5):1175–82. doi: 10.1016/j.brs.2020.05.013.
93. Giorgio J, Landau SM, Jagust WJ, Tino P, Kourtzi Z, Alzheimer’s Disease Neuroimaging Initiative. Modelling prognostic trajectories of cognitive decline due to Alzheimer’s disease. Neuroimage Clin. 2020;26:102199. doi: 10.1016/j.nicl.2020.102199.
94. Thung K-H, Yap P-T, Adeli E, Lee S-W, Shen D. Conversion and time-to-conversion predictions of mild cognitive impairment using low-rank affinity pursuit denoising and matrix completion. Med Image Anal. 2018;45:68–82. doi: 10.1016/j.media.2018.01.002.
95. Cox DR. Regression models and life-tables. Breakthroughs Stat. 1992;372:527–41.
96. Cox DR, Oakes D. Analysis of survival data. Boca Raton, FL: CRC Press; 1984.
97. Liu K, Chen K, Yao L, Guo X. Prediction of mild cognitive impairment conversion using a combination of independent component analysis and the Cox model. Front Hum Neurosci. 2017;11:33. doi: 10.3389/fnhum.2017.00033.
98. Li S, Okonkwo O, Albert M, Wang M-C. Variation in variables that predict progression from MCI to AD dementia over duration of follow-up. Am J Alzheimers Dis. 2013;2:12–28. doi: 10.7726/ajad.2013.1002.
99. Franzmeier N, Koutsouleris N, Benzinger T, Goate A, Karch CM, Fagan AM, et al. Predicting sporadic Alzheimer’s disease progression via inherited Alzheimer’s disease-informed machine-learning. Alzheimers Dement. 2020;16(3):501–11. doi: 10.1002/alz.12032.
100. Koch G, Belli L, Giudice TL, Lorenzo FD, Sancesario GM, Sorge R, et al. Frailty among Alzheimer’s disease patients. CNS Neurol Disord Drug Targets. 2013;12(4):507–11. doi: 10.2174/1871527311312040010.
101. Langa KM, Levine DA. The diagnosis and management of mild cognitive impairment: a clinical review. JAMA. 2014;312(23):2551–61. doi: 10.1001/jama.2014.13806.
102. Rosenberg PB, Lyketsos C. Mild cognitive impairment: searching for the prodrome of Alzheimer’s disease. World Psychiatry. 2008;7(2):72–8. doi: 10.1002/j.2051-5545.2008.tb00159.x.
103. Gamberger D, Lavrač N, Srivatsa S, Tanzi RE, Doraiswamy PM. Identification of clusters of rapid and slow decliners among subjects at risk for Alzheimer’s disease. Sci Rep. 2017;7:6763. doi: 10.1038/s41598-017-06624-y.
104. Gamberger D, Ženko B, Mitelpunkt A, Lavrač N. Homogeneous clusters of Alzheimer’s disease patient population. Biomed Eng Online. 2016;15(Suppl 1):78. doi: 10.1186/s12938-016-0183-0.
Downloads
Published
Issue
Section
License
Copyright (c) 2024 Khushboo Bansal, Shubhanshu Goel, Bhumika Chauhan, Shubh Deep Yadav, Ms. Fatima Zehra
This work is licensed under a Creative Commons Attribution 4.0 International License.
