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Potential Biomarkers for Early Diagnosis of Alzheimer’s Disease and Primary Open-Angle Glaucoma

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Alzheimer’s disease (AD) is a progressive neurodegenerative disease in which the clinical picture, in addition to cognitive and behavioral disorders, includes visual impairment. Amyloid-β (Aβ) deposits have also been found in the retina in AD patients. Primary open-angle glaucoma (POAG), which, like AD, is a neurodegenerative disease, occupies the leading position among geronto-ophthalmic pathologies in AD patients. AD and POAG have similar general features, so it should be possible to develop a number of general principles for the early diagnosis of these diseases. The search for biomarkers for the early detection of AD and POAG is promising. In the case of AD, early biomarkers in the cerebrospinal fluid and brain have now received extensive study by visualization of amyloid plaques and tau protein by positron emission tomography, while data on the use of these biomarkers in patients with POAG are rare in the literature. These diagnostic methods are not used in routine clinical practice due to their invasiveness and high cost. There is a growing need for simple, accessible biomarkers for AD and POAG, as treatment must begin at the prodromal stages of the disease, well before the onset of clinical symptoms. In AD patients, the role of biomarkers such as Aβ and tau protein in serum and plasma is under active investigation. In the case of patients with POAG, there are no data from studies of these biomarkers in the blood – further research is needed. Sirtuins (SIRT) have been found to play roles in aging and age-related diseases such as AD, glaucoma, macular degeneration, etc. SIRT may become biomarkers for neurodegenerative diseases.

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References

  1. A. P. Solov’eva, D. V. Goryachev, and V. V. Arkhipov, A. P. “Criteria for assessment of cognitive impairment in clinical trials,” Ved. Nauchn. Tsentr. Ekspert. Sredstv. Med. Primenen., 8, No. 4, 218–230 (2018), https://doi.org/10.30895/1991-2919-2018-8-4-218-230.

  2. N. Gupta, J. Fong, L. C. Ang, and Y. H. Yucel, “Retinal tau pathology in human glaucomas,” Can. J. Ophthalmol., 43, No. 1, 53–60 (2008), https://doi.org/10.3129/i07-185.

    Article  PubMed  Google Scholar 

  3. S. J. McKinnon, “Glaucoma: ocular Alzheimer’s disease,” Front. Biosci., 8, No. 11, 1140–1156 (2003), https://doi.org/10.2741/1172..

    Article  Google Scholar 

  4. Y. H. Yücel, N. Gupta, Q. Zhang, et al., “Loss of neurons in magnocellular and parvocellular layers of geniculate nucleus in glaucoma,” Arch. Ophthalmol., 118, No. 3, 378–384 (2000), https://doi.org/10.1001/ARCHOPHT.118.3.378.

    Article  PubMed  Google Scholar 

  5. C. R. Jack, Jr., D. S. Knopman, W. J. Jagust, et al., “Hypothetical model of dynamic biomarkers of the Alzheimer’s pathological cascade,” Lancet Neurol., 9, No. 1, 119–128 (2010), https://doi.org/10.1016/S1474-4422(09)70299-6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. N. J. Ashton, M. Schöll, K. Heurling, et al., “Update on biomarkers for amyloid pathology in Alzheimer’s disease,” Biomark Med., 12, No. 7, 799–812 (2018), https://doi.org/10.2217/bmm-2017-0433.

    Article  CAS  PubMed  Google Scholar 

  7. S. Janelidze, J. Pannee, A. Mikulskis, et al., “Concordance between different amyloid immunoassays and visual amyloid positron emission tomographic assessment,” JAMA Neurol., 74, No. 12, 1492–501 (2017), https://doi.org/10.1001/jamaneurol.2017.2814.

    Article  PubMed  PubMed Central  Google Scholar 

  8. A. A. Naumenko, D. O. Gromova, N. V. Trofimova, et al., “Diagnosis and treatment of Alzheimer’s disease,” Nevrol. Neiropsikh. Psikhosom., 8, No. 4, 91–97 (2016).

    Google Scholar 

  9. J. K. Lim, Q. X. Li, Z. He, et al., “The eye as a biomarker for Alzheimer’s disease,” Front. Neurosci., 17, No. 10, 536 (2016), https://doi.org/10.3389/fnins.2016.00536.

    Article  Google Scholar 

  10. S. A. Kozlovskii, B. B. Velichkovskii, A. V. Vartanov, et al., “The role of areas of the cingulate cortex in the functioning of human memory,” Eksperim. Psikhol., 5, No. 1, 12–22 (2012).

    Google Scholar 

  11. S. Gauthier, J. Cummings, C. Ballard, et al., “Management of behavioral problems in Alzheimer’s disease,” Int. Psychogeriatr., 22, No. 3, 346–72 (2010), https://doi.org/10.1017/S1041610209991505.

    Article  PubMed  Google Scholar 

  12. P. D. Bruen, W. J. McGeown, M. F. Shanks, and A. Venneri, “Neuroanatomical correlates of neuropsychiatric symptoms in Alzheimer’s disease,” Brain, 131, No. 9, 2455–2463 (2008), https://doi.org/10.1093/brain/awn151.

    Article  PubMed  Google Scholar 

  13. V. Yu. Lobzin, V. N. Kiselev, and V. A. Fokin, et al., “Application of magnetic resonance morphometry in the diagnosis of Alzheimer’s disease and vascular cognitive disorders,” Vestn. Ross. Voenno-Med. Akad., 3, 43 (2013).

    Google Scholar 

  14. A. U. Bayer, F. Ferrari, and C. Erg, “High occurrence rate of glaucoma among patients with Alzheimer’s disease,” Eur. Neurol., 47, No. 3, 165–168 (2002), https://doi.org/10.1159/000047976.

    Article  CAS  PubMed  Google Scholar 

  15. A. N. Bogolepova, E. V. Makhnovich, and A. N. Zhuravleva, “Comorbidity of Alzheimer’s disease and geronto-ophthalmic pathology,” Zh. Nevrol. Psikhiatr., 119, No. 9, 17–22 (2019), https://doi.org/10.17116/jnevro201911909117.

  16. A. N. Bogolepova, E. V. Makhnovich, and A. N. Zhuravleva, “The relationship between cognitive impairments and changes in retinal neuroarchitectonics,” Zh. Nevrol. Psikhiatr., 120, No. 9, 7–13 (2020), https://doi.org/10.17116/jnevro20201200917.

  17. R. A. Armstrong, “Visual field defects in Alzheimer’s disease patients may reflect differential pathology in the primary visual cortex,” Optom. Vis. Sci., 73, No. 11, 677–682 (1996), https://doi.org/10.1097/00006324-199611000-00001.

    Article  CAS  PubMed  Google Scholar 

  18. V. T. Chan, Z. Sun, S. Tang, et al., “Spectral-domain OCT measurements in Alzheimer’s disease: a systematic review and meta-analysis,” Ophthalmology, 126, No. 4, 497–510 (2019), https://doi.org/10.1016/j.ophtha.2018.08.009.

    Article  PubMed  Google Scholar 

  19. K. L. Thomson, J. R. Cameron, and S. Pal, “A systematic review and meta-analysis of retinal nerve fiber layer change in dementia, using optical coherence tomography,” Alzheimers Dement. Diagn., Assess. Dis. Monit., 1, No. 2, 136–143 (2015), https://doi.org/10.1016/j.dadm.2015.03.001.

    Article  Google Scholar 

  20. Y. Fu**o, M. W. Delucia, P. Davies, and D. W. Dickson, “Ballooned neurones in the limbic lobe are associated with Alzheimer type pathology and lack diagnostic specifi city,” Neuropathol. Appl. Neurobiol., 30, No. 6, 676–682 (2004).

    Article  CAS  PubMed  Google Scholar 

  21. V. P. Erichev, L. A. Panyushkina, and A. V. Fomin, “Optical coherence tomography of the retina and optic nerve in the diagnosis of Alzheimer’s disease,” Glaukoma, No. 1, 5–10 (2013).

    Google Scholar 

  22. B. Knoll, J. Simonett, N. J. Volpe, et al., “Retinal nerve fiber layer thickness in amnestic mild cognitive impairment: Case-control study and meta-analysis,” Alzheimers Dement., 4, No. 2, 85–93 (2016), https://doi.org/10.1016/j.dadm.2016.07.004.

    Article  Google Scholar 

  23. M. F. Mendez, J. Turner, G. C. Gilmore, et al., “Balint’s syndrome in Alzheimer’s disease: visuospatial functions,” Int. J. Neurosci., 54, No. 3–4, 339–346 (1990).

    Article  CAS  PubMed  Google Scholar 

  24. C. Criscuolo, E. Cerri, C. Fabiani, et al., “The retina as a window to early dysfunctions of Alzheimer’s disease following studies with a 5xFAD mouse model,” Neurobiol. Aging, 67, 181–188 (2018), https://doi.org/10.1016/j.neurobiolaging.2018.03.017.

    Article  CAS  PubMed  Google Scholar 

  25. M. Koronyo-Hamaoui, Y. Koronyo, A. V. Ljubimov, et al., “Identification of amyloid plaques in retinas from Alzheimer’s patients and noninvasive in vivo optical imaging of retinal plaques in a mouse model,” NeuroImage, 54, No. 1, 204–217 (2011).

    Article  Google Scholar 

  26. V. K. Gupta, N. Chitranshi, V. B. Gupta, et al., “Amyloid beta accumulation and inner retinal degenerative changes in Alzheimer’s disease transgenic mouse,” Neurosci. Lett., 623, 52–56 (2016).

    Article  CAS  PubMed  Google Scholar 

  27. Y. Koronyo, D. Biggs, E. Barron, et al., “Retinal amyloid pathology and proof-of-concept imaging trial in Alzheimer’s disease,” JCI Insight, 2, 93621 (2017), https://doi.org/10.1172/jci.insight.93621.

    Article  PubMed  Google Scholar 

  28. S. Lee, K. Jiang, B. McIlmoyle, et al., “Amyloid beta immunoreactivity in the retinal ganglion cell layer of the Alzheimer’s eye,” Front. Neurosci., 14, 758 (2020), https://doi.org/10.3389/fnins.2020.00758.

    Article  PubMed  PubMed Central  Google Scholar 

  29. M. C. La, F. N. Ross-Cisneros, Y. Koronyo, et al., “Melanopsin retinal ganglion cell loss in Alzheimer disease,” Ann. Neurol., 79, 90–109 (2016), https://doi.org/10.1002/ana.24548.

    Article  CAS  Google Scholar 

  30. J. den Haan, T. H. J. Morrema, F. D. Verbraak, et al., “Amyloid-beta and phosphorylated tau in post-mortem Alzheimer’s disease retinas,” Acta Neuropathol. Commun., 6, 147 (2018), https://doi.org/10.1186/s40478-018-0650-x.

    Article  CAS  Google Scholar 

  31. S. Yoneda, H. Hara, A. Hirata, et al., “Vitreous fl uid levels of beta-amyloid ((1-42)) and tau in patients with retinal diseases,” Jpn. J. Ophthalmol., 49, No. 2, 106–108 (2005), https://doi.org/10.1007/s10384-004-0156-x.

    Article  CAS  PubMed  Google Scholar 

  32. C. Nucci, A. Martucci, A. Martorana, et al., “Glaucoma progression associated with altered cerebral spinal fl uid levels of amyloid beta and tau proteins,” Clin. Exp. Ophthalmol., 39, No. 3, 279–281 (2011), https://doi.org/10.1111/j.1442-9071.2010.02452.x.

    Article  PubMed  Google Scholar 

  33. N. J. Ashton, A. Leuzy, T. K. Karikari, et al., “The validation status of blood biomarkers of amyloid and phospho-tau assessed with the 5-phase development framework for AD biomarkers,” Eur. J. Nucl. Med. Mol. Imag., 48, No. 7, 2140–2156 (2021), https://doi.org/10.1007/s00259-021-05253-y.

    Article  CAS  Google Scholar 

  34. N. Kaneko, A. Nakamura, Y. Washimi, et al., “A novel plasma biomarker surrogated by cerebral amyloid deposition,” Proc. Jpn. Acad. Ser. B Phys. Biol. Sci., 90, No. 9, 353–364 (2014), https://doi.org/10.2183/pjab.90.353.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. V. Ovod, K. N. Ramsey, K. G. Mawuenyega, et al., “Amyloid beta concentrations and stable isotope labeling kinetics of human plasma specific for central nervous system amyloidosis,” Alzheimers Dement., 13, No. 8, 841–849 (2017), https://doi.org/10.1016/j.jalz.2017.06.2266.

    Article  PubMed  PubMed Central  Google Scholar 

  36. A. Nakamura, N. Kaneko, V. L. Willemagne, et al., “Highly effective biomarkers of amyloid-beta in blood plasma for Alzheimer’s disease,” Nature, 554, No. 7691, 249–254 (2018), https://doi.org/10.1038/nature25456.

    Article  CAS  PubMed  Google Scholar 

  37. N. Fandos, V. Perez-Grijalba, P. Pesini, et al., “Plasma amyloid beta 42/40 ratios as biomarkers for amyloid beta cerebral deposition in cognitively normal individuals,” Alzheimers Dement. (Amst.), 8, 179–187 (2017), https://doi.org/10.1016/j.dadm.2017.07.004.

    Article  PubMed  Google Scholar 

  38. S. Janelidze, E. Stomrud, and S. Palmqvist, “Plasma beta-amyloid in Alzheimer’s disease and vascular disease,” Sci. Rep., 6, 26801 (2016), https://doi.org/10.1038/srep26801.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. A. Rembach, N. G. Faux, and A. D. Watt, “Changes in plasma amyloid beta in a longitudinal study of aging and Alzheimer’s disease,” Alzheimers Dement., 10, 53–61 (2014), https://doi.org/10.1016/j.jalz.2012.12.006.

    Article  PubMed  Google Scholar 

  40. J. B. Toledo, H. Vanderstichele, and M. Figurski, “Factors affecting Abeta plasma levels and their utility as biomarkers in ADNI,” Acta Neuropathol., 122, 401–413 (2011), https://doi.org/10.1007/s00401-011-0861-8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. D. P. Devanand, N. Schupf, and Y. Stern, “Plasma Abeta and PET PiB binding are inversely related in mild cognitive impairment,” Neurology, 77, 125–131 (2011), https://doi.org/10.1212/WNL.0b013e318224afb7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. J. K. Lui, S. M. Laws, and Q. X. Li, “Plasma amyloid-beta as a biomarker in Alzheimer’s disease: the AIBL study of aging,” J. Alzheimers Dis., 20, 1233–1242 (2010), https://doi.org/10.3233/JAD-2010-090249.

    Article  CAS  PubMed  Google Scholar 

  43. S. Swaminathan, S. L. Risacher, and K. K. Yoder, “Association of plasma and cortical amyloid beta is modulated by APOE epsilon4 status,” Alzheimers Dement., 10, 9–18 (2014), https://doi.org/10.1016/j.jalz.2013.01.007.

    Article  Google Scholar 

  44. V. Perez-Grijalba, J. Romero, and P. Pesini, “Plasma Aβ42/40 ratio detects early stages of Alzheimer’s disease and correlates with CSF and neuroimaging biomarkers in the AB255 study,” J. Prev. Alzheimers Dis., 6, 34–41 (2019), https://doi.org/10.14283/jpad.2018.41.

    Article  CAS  PubMed  Google Scholar 

  45. S. Palmqvist, S. Janelidze, E. Stomrud, et al., “Performance of fully automated plasma assays as screening tests for Alzheimer disease-related beta-amyloid status,” JAMA Neurol., 76, No. 9, 1060–1069 (2019), https://doi.org/10.1001/jamaneurol.2019.1632.

    Article  PubMed  PubMed Central  Google Scholar 

  46. K. Yaffe, A. Weston, and N. R. Graff-Radford, “Association of plasma beta-amyloid level and cognitive reserve with subsequent cognitive decline,” JAMA, 305, 261–266 (2011), https://doi.org/10.1001/jamaneurol.2019.1632.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. L. Abdullah, C. Luis, and D. Paris, “Serum Abeta levels as predictors of conversion to mild cognitive impairment in an ADAPT subcohort,” Mol. Med., 15, 432–437 (2009), https://doi.org/10.2119/molmed.2009.00083.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. V. Chouraki, A. Beiser, and L. Younkin, “Plasma amyloid-beta and risk of Alzheimer’s disease in the Framingham Heart Study,” Alzheimers Dement., 11, 249–257 (2015), https://doi.org/10.1016/j.jalz.2014.07.001.

    Article  PubMed  Google Scholar 

  49. N. R. Graff-Radford, J. E. Crook, and J. Lucas, “Association of low plasma Abeta42/Abeta40 ratios with increased imminent risk for mild cognitive impairment and Alzheimer disease,” Arch. Neurol., 64, 354–362 (2007), https://doi.org/10.1001/archneur.64.3.354.

    Article  PubMed  Google Scholar 

  50. J. C. Lambert, S. Schraen-Maschke, and F. Richard, “Association of plasma amyloid beta with risk of dementia: the prospective Three-City Study,” Neurology, 73, 847–853 (2009), https://doi.org/10.1212/WNL.0b013e3181b78448.

    Article  CAS  PubMed  Google Scholar 

  51. M. van Oijen, A. Hofman, H. D. Soares, et al., “Plasma Abeta(1-40) and Abeta(1-42) and the risk of dementia: a prospective case-cohort study,” Lancet Neurol., 5, 655–660 (2006), https://doi.org/10.1016/S1474-4422(06)70501-4.

    Article  PubMed  Google Scholar 

  52. J. D. Doecke, V. Pérez-Grijalba, N. Fandos, et al., AIBL Research Group, “Total Aβ42/Aβ40 ratio in plasma predicts amyloid-PET status, independent of clinical AD diagnosis,” Neurology, 94, No. 15, 1580–1589 (2020), https://doi.org/10.1212/WNL.0000000000009240.

  53. A. Benussi, T. K. Karikari, N. Ashton, et al., “Diagnostic and prognostic value of serum NfL and p-Tau181 in frontotemporal lobar degeneration,” J. Neurol. Neurosurg. Psychiatry, 91, No. 9, 960–967 (2020), https://doi.org/10.1136/jnnp-2020-323487.

    Article  PubMed  Google Scholar 

  54. E. H. Thijssen, R. La Joie, A. Wolf, et al., “Treatment for frontotemporal lobar degeneration, diagnostic value of plasma phosphorylated tau181 in Alzheimer’s disease and frontotemporal lobar degeneration,” Nat. Med., 26, No. 3, 387–297 (2020), https://doi.org/10.1038/s41591-020-0762-2.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. S. Palmqvist, S. Janelidze, Y. T. Quiroz, et al., “Discriminative accuracy of plasma phospho-tau217 for Alzheimer disease vs other neurodegenerative disorders,” JAMA, 324, No. 8, 772–781 (2020), https://doi.org/10.1001/jama.2020.12134.

    Article  CAS  PubMed  Google Scholar 

  56. S. Janelidze, N. Mattsson, S. Palmqvist, 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., 26, No. 3, 379–386 (2020), https://doi.org/10.1038/s41591-020-0755-1.

    Article  CAS  PubMed  Google Scholar 

  57. J. Lantero Rodriguez, T. K. Karikari, M. Suarez-Calvet, et al., “Plasma p-tau181 predicts Alzheimer’s disease pathology at least 8 years prior to post-mortem and improves the clinical characterisation of cognitive decline,” Acta Neuropathol., 140, No. 3, 267–278 (2020), https://doi.org/10.1007/s00401-020-02195-x.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. J. Simrén, A. Leuzy, et al., “The diagnostic and prognostic capabilities of plasma biomarkers in Alzheimer’s disease,” Alzheimers Dement., 17, No. 7, 1145–1156 (2021), https://doi.org/10.1002/alz.12283.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. H. Jęśko, P. Wencel, R. P. Strosznajder, et al., “Sirtuins and their roles in brain aging and neurodegenerative disorders,” Neurochem. Res., 42, No. 3, 876–890 (2017), https://doi.org/10.1007/s11064-016-2110-y.

    Article  CAS  PubMed  Google Scholar 

  60. B. Morris, “Seven sirtuins for seven deadly diseases of aging,” Free Radic. Biol. Med., 56, 133–171 (2013), https://doi.org/10.1016/j.freeradbiomed.2012.10.525.

    Article  CAS  PubMed  Google Scholar 

  61. T. Finkel, C.-X. Deng, and R. Mostoslavsky, “Recent progress in the biology and physiology of sirtuins,” Nature, 460, No. 72550, 587–591 (2009), https://doi.org/10.1038/nature08197.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. S. Balaiya, K. K. Abu-Amero, A. A. Kondkar, and K. V. Chalam, “Sirtuins expression and their role in retinal diseases,” Oxid. Med. Cell. Longev., 2017, 3187594 (2017), https://doi.org/10.1155/2017/3187594.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. A. N. Kahraman, and H. Z. Toklu, “The effects of sirtuin activators on cerebral white matter, redox biomarkers, and imaging findings in aging brain,” in: Redox Signaling and Biomarkers in Ageing, U. Çakatay (ed.), Series: Healthy Ageing and Longevity, Springer, Champaign (2022), Vol. 15, pp. 303–322, https://doi.org/10.1007/978-3-030-84965-8_14.

  64. R. Pradhan, A. K. Singh, P. Kumar, et al., “Blood circulatory level of seven sirtuins in Alzheimer’s disease: Potent biomarker based on translational research,” Mol. Neurobiol., 7, 34–39 (2022), https://doi.org/10.1007/s12035-021-02671-9.

    Article  CAS  Google Scholar 

  65. C. Julien, C. Tremblay, V. Émond, et al., “Sirtuin 1 reduction parallels the accumulation of tau in Alzheimer disease,” J. Neuropathol. Exp. Neurol., 68, No. 1, 48–58 (2009), https://doi.org/10.1097/NEN.0b013e3181922348.

    Article  CAS  PubMed  Google Scholar 

  66. T. Y. Alhazzazi, P. Kamarajan, E. Verdin, and Y. L. Kapila, “Sirtuin-3 (SIRT3) and the hallmarks of cancer,” Genes Cancer, 4, 164–171 (2013), https://doi.org/10.1177/1947601913486351.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. M. D. Hirschey, T. Shimazu, J. Y. Huang, et al., “SIRT3 regulates mitochondrial protein acetylation and intermediary metabolism,” Cold Spring Harb. Symp. Quant. Biol., 76, 267–277 (2011), https://doi.org/10.1101/sqb.2011.76.010850.

    Article  CAS  PubMed  Google Scholar 

  68. N. Mattsson, P. S. Insel, P. S. Aisen, et al., “Brain structure and function as mediators of the effects of amyloid on memory,” Neurology, 84, 1136–1144 (2015), https://doi.org/10.1212/WNL.0000000000001375.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. R. Ossenkoppele, W. M. van der Flier, S. C. Verfaillie, et al., “Longterm effects of amyloid, hypometabolism, and atrophy on neuropsychological functions,” Neurology, 82, 1768–1775 (2014), https://doi.org/10.1212/WNL.0000000000000432.

    Article  CAS  PubMed  Google Scholar 

  70. E. Klupp, T. Grimmer, M. Tahmasian, et al., “Prefrontal hypometabolism in Alzheimer disease is related to longitudinal amyloid accumulation in remote brain regions,” J. Nucl. Med., 56, 399–404 (2015), https://doi.org/10.2967/jnumed.114.149302.

    Article  CAS  PubMed  Google Scholar 

  71. R. J. Laforce, D. Tosun, P. Ghosh, et al., “Parallel ICA of FDG-PET and PiB-PET in three conditions with underlying Alzheimer’s pathology,” NeuroImage Clin., 4, 508–516 (2014), https://doi.org/10.1016/j.nicl.2014.03.005.

    Article  PubMed  PubMed Central  Google Scholar 

  72. G. E. Alexander, K. Chen, et al., “Longitudinal PET evaluation of cerebral metabolic decline in dementia: a potential outcome measure in Alzheimer’s disease treatment studies,” Am. J. Psychiatry, 159, 738–745 (2002), https://doi.org/10.1176/appi.ajp.159.5.738.

    Article  PubMed  Google Scholar 

  73. E. M. Reiman, R. J. Caselli, L. S. Yun, et al., “Preclinical evidence of Alzheimer’s disease in persons homozygous for the epsilon 4 allele for apolipoprotein E,” N. Engl. J. Med., 334, 752–758 (1996), https://doi.org/10.1056/NEJM199603213341202.

    Article  CAS  PubMed  Google Scholar 

  74. J. Yin, P. Han, M. Song, et al., “Amyloid-β increases 2882 tau by mediating sirtuin 3 in Alzheimer’s disease,” Mol. Neurobiol., 55, 8592–8601 (2018), https://doi.org/10.1007/s12035-018-0977-0.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. P. Han, Z. Tang, J. Yin, et al., “Pituitary adenylate cyclase-activating polypeptide protects against β-amyloid toxicity,” Neurobiol. Aging, 35, 2064–2071 (2014), https://doi.org/10.1016/j.neurobiolaging.2014.03.022.

    Article  CAS  PubMed  Google Scholar 

  76. J. X. Yin, M. Maalouf, P. Han, et al., “Ketones block amyloid entry and improve cognition in an Alzheimer’s model,” Neurobiol. Aging, 39, 25–37 (2016), https://doi.org/10.1016/j.neurobiolaging.2015.11.018.

    Article  CAS  PubMed  Google Scholar 

  77. D. Toiber, F. Erdel, K. Bouazoune, et al., “SIRT6 recruits SNF2H to DNA break sites, preventing genomic instability through chromatin remodeling,” Mol. Cell, 51, 454–468 (2013), https://doi.org/10.1016/j.molcel.2013.06.018.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. S. Kaluski, M. Portillo, A. Besnard, et al., “Neuroprotective functions for the histone deacetylase SIRT6,” Cell Rep., 18, No. 13, 3052–3062 (2017), https://doi.org/10.1016/j.celrep.2017.03.008.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  79. N. F. Mohamad Nasir, A. Zainuddin, and S. Shamsuddin, “Emerging roles of Sirtuin 6 in Alzheimer’s disease,” J. Mol. Neurosci., 64, No. 2, 157–161 (2018), https://doi.org/10.1007/s12031-017-1005-y.

    Article  CAS  PubMed  Google Scholar 

  80. A. E. Pukhalskaia, A. S. Dyatlova, N. S. Linkova, et al., “Sirtuins as possible predictors of aging and Alzheimer’s disease development: Verifi cation in the hippocampus and saliva,” Bull. Exp. Biol. Med., 169, No. 6, 821–824 (2020), https://doi.org/10.1007/s10517-020-04986-4.

    Article  CAS  PubMed  Google Scholar 

  81. J. Yang, X. Kong, M. E. Martins-Santos, et al., “Activation of SIRT1 by resveratrol represses transcription of the gene for cytosolic form of phosphoenolpyruvate carboxykinase by deacetylating hepatic nuclear factor 4α*,” J. Biol. Chem., 284, 27042–27053 (2009), https://doi.org/10.1074/jbc.M109.047340.

    Article  PubMed  PubMed Central  Google Scholar 

  82. E. Sidorova-Darmos, R. G. Wither, N. Shulyakova, et al., “Differential expression of sirtuin family members in the develo**, adult, and aged rat brain,” Front. Aging Neurosci., 18, No. 6, 333 (2014), https://doi.org/10.3389/fnagi.2014.00333.

    Article  Google Scholar 

  83. A. Ames, 3rd and Y. Y. Li, “Energy requirements of glutamatergic pathways in rabbit retina,” J. Neurosci., 12, No. 11, 4234–4142 (1992), https://doi.org/10.1523/JNEUROSCI.12-11-04234.1992.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. J. E. Niven and S. B. Laughlin, “Energy limitation as a selective pressure on the evolution of sensory systems,” J. Exp. Biol., 211, No. 11, 1792–804 (2008), https://doi.org/10.1242/jeb.017574.

    Article  CAS  PubMed  Google Scholar 

  85. N. Ban, Y. Ozawa, T. Inaba, et al., “Light-dark condition regulates sirtuin mRNA levels in the retina,” Exp. Gerontol., 48, No. 11, 1212–1217 (2013), https://doi.org/10.1016/j.exger.2013.04.010.

    Article  CAS  PubMed  Google Scholar 

  86. C. H. Peng, Y. L. Chang, C. L. Kao, et al., “SirT1-A sensor for monitoring self-renewal and aging process in retinal stem cells,” Sensors (Basel), 10, 6172–6194 (2010), https://doi.org/10.3390/s100606172.

    Article  CAS  PubMed  Google Scholar 

  87. T. Mimura, Y. Kaji, H. Noma, et al., “The role of SIRT1 in ocular aging,” Exp. Eye Res., 34, No. 8, 11617–11626 (2013), https://doi.org/10.1016/j.exer.2013.07.017.

    Article  CAS  Google Scholar 

  88. Y. Zeng and K. Yang, “Sirtuin 1 participates in the process of age-related retinal degeneration,” Biochem. Biophys. Res. Commun., 468, No. 1–2, 167–172 (2015), https://doi.org/10.1016/j.bbrc.2015.10.139.

    Article  CAS  PubMed  Google Scholar 

  89. A. Trovato Salinaro, C. Cornelius, and G. Koverech, “Cellular stress response, redox status, and vitagenes in glaucoma: a systemic oxidant disorder linked to Alzheimer’s disease,” Front. Pharmacol., 5, 29–32 (2014), https://doi.org/10.3389/fphar.2014.00129.

    Article  CAS  Google Scholar 

  90. A. Yucel Gencoglu, M. Irkec, S. Kocabeyoglu, et al., “Plasma levels of sirtuin and adiponectin in patients with primary open-angle glaucoma, exfoliative glaucoma, and healthy controls,” Eur. J. Ophthalmol., 8, 11206721211065216 (2021), https://doi.org/10.1177/11206721211065216.

    Article  Google Scholar 

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Correspondence to E. V. Makhnovich.

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Translated from Zhurnal Nevrologii i Psikhiatrii imeni S. S. Korsakova, Vol. 122, No. 9, pp. 7–14, September, 2022.

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Bogolepova, A.N., Makhnovich, E.V., Kovalenko, E.A. et al. Potential Biomarkers for Early Diagnosis of Alzheimer’s Disease and Primary Open-Angle Glaucoma. Neurosci Behav Physi 53, 509–516 (2023). https://doi.org/10.1007/s11055-023-01449-x

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