Detection of early-stage Alzheimer’s pathology using blood-based autoantibody biomarkers in elderly hip fracture repair patients

Autoři: Cassandra DeMarshall aff001;  Esther Oh aff003;  Rahil Kheirkhah aff005;  Frederick Sieber aff004;  Henrik Zetterberg aff006;  Kaj Blennow aff006;  Robert G. Nagele aff001
Působiště autorů: Biomarker Discovery Center, New Jersey Institute for Successful Aging, Rowan University School of Osteopathic Medicine, Stratford, New Jersey, United States of America aff001;  Department of Geriatrics and Gerontology, Rowan University School of Osteopathic Medicine, Stratford, New Jersey, United States of America aff002;  Department of Medicine, Psychiatry and Behavioral Sciences, Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America aff003;  Department of Anesthesiology and Critical Care Medicine, Johns Hopkins Bayview Medical Center, Baltimore, Maryland, United States of America aff004;  Graduate School of Biomedical Sciences (GSBS), Rowan University, Stratford, New Jersey, United States of America aff005;  Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden aff006;  Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden aff007;  Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, Queen Square, London, England, United Kingdom aff008;  UK Dementia Research Institute at UCL, London, England, United Kingdom aff009
Vyšlo v časopise: PLoS ONE 14(11)
Kategorie: Research Article
doi: 10.1371/journal.pone.0225178


Post-operative delirium (POD) is the most common complication following major surgery in non-demented older (>65 y/o) patients. Patients experiencing POD show increased risk for future cognitive decline, including mild cognitive impairment (MCI) and Alzheimer’s disease (AD) and, conversely, patients with cognitive decline at surgery show increased risk for POD. Here, we demonstrate that a previously established panel of AD-driven MCI (ADMCI) autoantibody (aAB) biomarkers can be used to detect prodromal AD pre-surgically in individuals admitted into the hospital for hip fracture repair (HFR) surgery. Plasma from 39 STRIDE (STRIDE: A Strategy to Reduce the Incidence of Postoperative Delirium in Elderly Patients) HFR patients and sera from 25 age- and sex-matched non-demented and non-surgical controls were screened using human protein microarrays to measure expression of a panel of 44 previously identified MCI aAB biomarkers. The predictive classification accuracy of the aAB biomarker panel was evaluated using Random Forest (RF). The ADMCI aAB biomarkers successfully distinguished 21 STRIDE HFR patients (CDR = 0.5) from 25 matched non-surgical controls with an overall accuracy of 91.3% (sensitivity = 95.2%; specificity = 88.0%). The ADMCI aAB panel also correctly identified six patients with preoperative CDR = 0 who later converted to CDR = 0.5 or >1 at one-year follow-up. Lastly, the majority of cognitively normal (CDR = 0) STRIDE HFR subjects that were positive for CSF AD biomarkers based on the A/T/N classification system were likewise classified as ADMCI aAB-positive using the biomarker panel. Results suggest that pre-surgical detection of ADMCI aAB biomarkers can readily identify HFR patients with likely early-stage AD pathology using pre-surgery blood samples, opening up the potential for early, blood-based AD detection and improvements in peri- and postoperative patient management.

Klíčová slova:

Alzheimer's disease – Biomarkers – Blood – Cerebrospinal fluid – Cognitive impairment – Microarrays – Surgical and invasive medical procedures – Hemorrhagic fever with renal syndrome


1. Trojanowski JQ, Hampel H. Neurodegenerative disease biomarkers: guideposts for disease prevention through early diagnosis and intervention. Prog Neurobiol. 2011;95(4):491–5. Epub 2011/08/09. doi: 10.1016/j.pneurobio.2011.07.004 21821094; PubMed Central PMCID: PMCPMC3575085.

2. 2019 Alzheimer's disease facts and figures. Alzheimer's & Dementia. 2019;15(3):321–87.

3. Blennow K, de Leon MJ, Zetterberg H. Alzheimer's disease. Lancet. 2006;368(9533):387–403. Epub 2006/08/01. doi: 10.1016/S0140-6736(06)69113-7 16876668.

4. Casey DA, Antimisiaris D, O'Brien J. Drugs for Alzheimer's disease: are they effective? P T. 2010;35(4):208–11. Epub 2010/05/26. 20498822; PubMed Central PMCID: PMCPMC2873716.

5. 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(9):795–804. Epub 2012/07/13. doi: 10.1056/NEJMoa1202753 22784036; PubMed Central PMCID: PMCPMC3474597.

6. Braak H, Braak E. Frequency of stages of Alzheimer-related lesions in different age categories. Neurobiol Aging. 1997;18(4):351–7. Epub 1997/07/01. doi: 10.1016/s0197-4580(97)00056-0 9330961.

7. de Leon MJ, Convit A, Wolf OT, Tarshish CY, DeSanti S, Rusinek H, et al. Prediction of cognitive decline in normal elderly subjects with 2-[(18)F]fluoro-2-deoxy-D-glucose/poitron-emission tomography (FDG/PET). Proc Natl Acad Sci U S A. 2001;98(19):10966–71. Epub 2001/08/30. doi: 10.1073/pnas.191044198 11526211; PubMed Central PMCID: PMCPMC58582.

8. Hulette CM, Welsh-Bohmer KA, Murray MG, Saunders AM, Mash DC, McIntyre LM. Neuropathological and neuropsychological changes in "normal" aging: evidence for preclinical Alzheimer disease in cognitively normal individuals. J Neuropathol Exp Neurol. 1998;57(12):1168–74. Epub 1998/12/23. doi: 10.1097/00005072-199812000-00009 9862640.

9. Morris JC, Storandt M, McKeel DW Jr., Rubin EH, Price JL, Grant EA, et al. Cerebral amyloid deposition and diffuse plaques in "normal" aging: Evidence for presymptomatic and very mild Alzheimer's disease. Neurology. 1996;46(3):707–19. Epub 1996/03/01. doi: 10.1212/wnl.46.3.707 8618671.

10. Price JL, Morris JC. Tangles and plaques in nondemented aging and "preclinical" Alzheimer's disease. Ann Neurol. 1999;45(3):358–68. Epub 1999/03/11. doi: 10.1002/1531-8249(199903)45:3<358::aid-ana12>;2-x 10072051.

11. Petersen RC. Early diagnosis of Alzheimer's disease: is MCI too late? Curr Alzheimer Res. 2009;6(4):324–30. Epub 2009/08/20. doi: 10.2174/156720509788929237 19689230; PubMed Central PMCID: PMCPMC3098139.

12. Blennow K, Dubois B, Fagan AM, Lewczuk P, de Leon MJ, Hampel H. Clinical utility of cerebrospinal fluid biomarkers in the diagnosis of early Alzheimer's disease. Alzheimers Dement. 2015;11(1):58–69. Epub 2014/05/06. doi: 10.1016/j.jalz.2014.02.004 24795085; PubMed Central PMCID: PMCPMC4386839.

13. van der Vlies AE, Verwey NA, Bouwman FH, Blankenstein MA, Klein M, Scheltens P, et al. CSF biomarkers in relationship to cognitive profiles in Alzheimer disease. Neurology. 2009;72(12):1056–61. Epub 2009/03/25. doi: 10.1212/01.wnl.0000345014.48839.71 19307538.

14. Petersen RC, Smith GE, Waring SC, Ivnik RJ, Tangalos EG, Kokmen E. Mild cognitive impairment: clinical characterization and outcome. Arch Neurol. 1999;56(3):303–8. Epub 1999/04/06. doi: 10.1001/archneur.56.3.303 10190820.

15. Albert MS, DeKosky ST, Dickson D, Dubois B, Feldman HH, Fox NC, et al. The diagnosis of mild cognitive impairment due to Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimers Dement. 2011;7(3):270–9. Epub 2011/04/26. doi: 10.1016/j.jalz.2011.03.008 21514249; PubMed Central PMCID: PMCPMC3312027.

16. Henriksen K, O'Bryant SE, Hampel H, Trojanowski JQ, Montine TJ, Jeromin A, et al. The future of blood-based biomarkers for Alzheimer's disease. Alzheimers Dement. 2014;10(1):115–31. Epub 2013/07/16. doi: 10.1016/j.jalz.2013.01.013 23850333; PubMed Central PMCID: PMCPMC4128378.

17. Cummings JL. Biomarkers in Alzheimer's disease drug development. Alzheimers Dement. 2011;7(3):e13–44. Epub 2011/05/10. doi: 10.1016/j.jalz.2010.06.004 21550318.

18. Blennow K, Hampel H, Weiner M, Zetterberg H. Cerebrospinal fluid and plasma biomarkers in Alzheimer disease. Nat Rev Neurol. 2010;6(3):131–44. Epub 2010/02/17. doi: 10.1038/nrneurol.2010.4 20157306.

19. Janelidze S, Zetterberg H, Mattsson N, Palmqvist S, Vanderstichele H, Lindberg O, et al. CSF Abeta42/Abeta40 and Abeta42/Abeta38 ratios: better diagnostic markers of Alzheimer disease. Ann Clin Transl Neurol. 2016;3(3):154–65. Epub 2016/04/05. doi: 10.1002/acn3.274 27042676; PubMed Central PMCID: PMCPMC4774260.

20. Mattsson N, Blennow K, Zetterberg H. CSF biomarkers: pinpointing Alzheimer pathogenesis. Ann N Y Acad Sci. 2009;1180:28–35. Epub 2009/11/13. doi: 10.1111/j.1749-6632.2009.04944.x 19906258.

21. Kang JH, Korecka M, Toledo JB, Trojanowski JQ, Shaw LM. Clinical utility and analytical challenges in measurement of cerebrospinal fluid amyloid-beta(1–42) and tau proteins as Alzheimer disease biomarkers. Clin Chem. 2013;59(6):903–16. Epub 2013/03/23. doi: 10.1373/clinchem.2013.202937 23519967; PubMed Central PMCID: PMCPMC4159709.

22. Morris GP, Clark IA, Vissel B. Inconsistencies and controversies surrounding the amyloid hypothesis of Alzheimer's disease. Acta Neuropathol Commun. 2014;2:135. Epub 2014/09/19. doi: 10.1186/s40478-014-0135-5 25231068; PubMed Central PMCID: PMCPMC4207354.

23. Hansson O, Seibyl J, Stomrud E, Zetterberg H, Trojanowski JQ, Bittner T, et al. CSF biomarkers of Alzheimer's disease concord with amyloid-beta PET and predict clinical progression: A study of fully automated immunoassays in BioFINDER and ADNI cohorts. Alzheimers Dement. 2018;14(11):1470–81. Epub 2018/03/03. doi: 10.1016/j.jalz.2018.01.010 29499171; PubMed Central PMCID: PMCPMC6119541.

24. Fagan AM, Shaw LM, Xiong C, Vanderstichele H, Mintun MA, Trojanowski JQ, et al. Comparison of analytical platforms for cerebrospinal fluid measures of beta-amyloid 1–42, total tau, and p-tau181 for identifying Alzheimer disease amyloid plaque pathology. Arch Neurol. 2011;68(9):1137–44. Epub 2011/05/11. doi: 10.1001/archneurol.2011.105 21555603; PubMed Central PMCID: PMCPMC3154969.

25. Tapiola T, Alafuzoff I, Herukka SK, Parkkinen L, Hartikainen P, Soininen H, et al. Cerebrospinal fluid {beta}-amyloid 42 and tau proteins as biomarkers of Alzheimer-type pathologic changes in the brain. Arch Neurol. 2009;66(3):382–9. Epub 2009/03/11. doi: 10.1001/archneurol.2008.596 19273758.

26. 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(1):45–58. Epub 2016/11/22. doi: 10.1016/j.jalz.2016.09.014 27870940; PubMed Central PMCID: PMCPMC5218961.

27. O'Bryant SE, Xiao G, Barber R, Huebinger R, Wilhelmsen K, Edwards M, et al. A blood-based screening tool for Alzheimer's disease that spans serum and plasma: findings from TARC and ADNI. PLoS One. 2011;6(12):e28092. Epub 2011/12/14. doi: 10.1371/journal.pone.0028092 22163278; PubMed Central PMCID: PMCPMC3233542.

28. O'Bryant SE, Gupta V, Henriksen K, Edwards M, Jeromin A, Lista S, et al. Guidelines for the standardization of preanalytic variables for blood-based biomarker studies in Alzheimer's disease research. Alzheimers Dement. 2015;11(5):549–60. Epub 2014/10/06. doi: 10.1016/j.jalz.2014.08.099 25282381; PubMed Central PMCID: PMCPMC4414664.

29. Sattlecker M, Kiddle SJ, Newhouse S, Proitsi P, Nelson S, Williams S, et al. Alzheimer's disease biomarker discovery using SOMAscan multiplexed protein technology. Alzheimers Dement. 2014;10(6):724–34. Epub 2014/04/29. doi: 10.1016/j.jalz.2013.09.016 24768341.

30. Mapstone M, Cheema AK, Fiandaca MS, Zhong X, Mhyre TR, MacArthur LH, et al. Plasma phospholipids identify antecedent memory impairment in older adults. Nat Med. 2014;20(4):415–8. Epub 2014/03/13. doi: 10.1038/nm.3466 24608097; PubMed Central PMCID: PMCPMC5360460.

31. Shahpasand-Kroner H, Klafki HW, Bauer C, Schuchhardt J, Huttenrauch M, Stazi M, et al. A two-step immunoassay for the simultaneous assessment of Abeta38, Abeta40 and Abeta42 in human blood plasma supports the Abeta42/Abeta40 ratio as a promising biomarker candidate of Alzheimer's disease. Alzheimers Res Ther. 2018;10(1):121. Epub 2018/12/12. doi: 10.1186/s13195-018-0448-x 30526652; PubMed Central PMCID: PMCPMC6286509.

32. Pase MP, Beiser AS, Himali JJ, Satizabal CL, Aparicio HJ, DeCarli C, et al. Assessment of Plasma Total Tau Level as a Predictive Biomarker for Dementia and Related Endophenotypes. JAMA Neurol. 2019;76(5):598–606. Epub 2019/03/05. doi: 10.1001/jamaneurol.2018.4666 30830207; PubMed Central PMCID: PMCPMC6515589.

33. Kiddle SJ, Sattlecker M, Proitsi P, Simmons A, Westman E, Bazenet C, et al. Candidate blood proteome markers of Alzheimer's disease onset and progression: a systematic review and replication study. J Alzheimers Dis. 2014;38(3):515–31. Epub 2013/10/15. doi: 10.3233/JAD-130380 24121966.

34. Cheng L, Quek CY, Sun X, Bellingham SA, Hill AF. The detection of microRNA associated with Alzheimer's disease in biological fluids using next-generation sequencing technologies. Front Genet. 2013;4:150. Epub 2013/08/22. doi: 10.3389/fgene.2013.00150 23964286; PubMed Central PMCID: PMCPMC3737441.

35. Nagele EP, Han M, Acharya NK, DeMarshall C, Kosciuk MC, Nagele RG. Natural IgG autoantibodies are abundant and ubiquitous in human sera, and their number is influenced by age, gender, and disease. PLoS One. 2013;8(4):e60726. Epub 2013/04/17. doi: 10.1371/journal.pone.0060726 23589757; PubMed Central PMCID: PMCPMC3617628.

36. DeMarshall CA, Han M, Nagele EP, Sarkar A, Acharya NK, Godsey G, et al. Potential utility of autoantibodies as blood-based biomarkers for early detection and diagnosis of Parkinson's disease. Immunol Lett. 2015;168(1):80–8. Epub 2015/09/20. doi: 10.1016/j.imlet.2015.09.010 26386375.

37. DeMarshall CA, Nagele EP, Sarkar A, Acharya NK, Godsey G, Goldwaser EL, et al. Detection of Alzheimer's disease at mild cognitive impairment and disease progression using autoantibodies as blood-based biomarkers. Alzheimers Dement (Amst). 2016;3:51–62. Epub 2016/05/31. doi: 10.1016/j.dadm.2016.03.002 27239548; PubMed Central PMCID: PMCPMC4879649.

38. Han M, Nagele E, DeMarshall C, Acharya N, Nagele R. Diagnosis of Parkinson's disease based on disease-specific autoantibody profiles in human sera. PLoS One. 2012;7(2):e32383. Epub 2012/03/03. doi: 10.1371/journal.pone.0032383 22384236; PubMed Central PMCID: PMCPMC3285212.

39. Nagele E, Han M, Demarshall C, Belinka B, Nagele R. Diagnosis of Alzheimer's disease based on disease-specific autoantibody profiles in human sera. PLoS One. 2011;6(8):e23112. Epub 2011/08/10. doi: 10.1371/journal.pone.0023112 21826230; PubMed Central PMCID: PMCPMC3149629.

40. DeMarshall C, Goldwaser EL, Sarkar A, Godsey GA, Acharya NK, Thayasivam U, et al. Autoantibodies as diagnostic biomarkers for the detection and subtyping of multiple sclerosis. J Neuroimmunol. 2017;309:51–7. Epub 2017/06/12. doi: 10.1016/j.jneuroim.2017.05.010 28601288.

41. Sieber FE, Neufeld KJ, Gottschalk A, Bigelow GE, Oh ES, Rosenberg PB, et al. Effect of Depth of Sedation in Older Patients Undergoing Hip Fracture Repair on Postoperative Delirium: The STRIDE Randomized Clinical Trial. JAMA Surg. 2018;153(11):987–95. Epub 2018/08/10. doi: 10.1001/jamasurg.2018.2602 30090923; PubMed Central PMCID: PMCPMC6583071.

42. Oh ES, Blennow K, Bigelow GE, Inouye SK, Marcantonio ER, Neufeld KJ, et al. Abnormal CSF amyloid-beta42 and tau levels in hip fracture patients without dementia. PLoS One. 2018;13(9):e0204695. Epub 2018/09/27. doi: 10.1371/journal.pone.0204695 30252906; PubMed Central PMCID: PMCPMC6155555 of our co-authors Dr. Zetterberg is a co-founder of Brain Biomarker Solutions in Gothenburg AB, a GU Ventures-based platform company at the University of Gothenberg, and has served at advisory boards of Roche Diagnostics and Eli Lilly and has received travel support from TEVA. We confirm that this does not alter our adherence to PLOS ONE policies on sharing data and materials.

43. Li T, Wieland LS, Oh E, Neufeld KJ, Wang NY, Dickersin K, et al. Design considerations of a randomized controlled trial of sedation level during hip fracture repair surgery: a strategy to reduce the incidence of postoperative delirium in elderly patients. Clin Trials. 2017;14(3):299–307. Epub 2017/01/11. doi: 10.1177/1740774516687253 28068834; PubMed Central PMCID: PMCPMC5446288.

44. Folstein MF, Folstein SE, McHugh PR. "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975;12(3):189–98. Epub 1975/11/01. doi: 10.1016/0022-3956(75)90026-6 1202204.

45. Jorm AF. A short form of the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE): development and cross-validation. Psychol Med. 1994;24(1):145–53. Epub 1994/02/01. doi: 10.1017/s003329170002691x 8208879.

46. Jack CR Jr., Wiste HJ, Weigand SD, Therneau TM, Knopman DS, Lowe V, et al. Age-specific and sex-specific prevalence of cerebral beta-amyloidosis, tauopathy, and neurodegeneration in cognitively unimpaired individuals aged 50–95 years: a cross-sectional study. Lancet Neurol. 2017;16(6):435–44. Epub 2017/05/01. doi: 10.1016/S1474-4422(17)30077-7 28456479; PubMed Central PMCID: PMCPMC5516534.

47. Jack CR Jr., Bennett DA, Blennow K, Carrillo MC, Feldman HH, Frisoni GB, et al. A/T/N: An unbiased descriptive classification scheme for Alzheimer disease biomarkers. Neurology. 2016;87(5):539–47. Epub 2016/07/03. doi: 10.1212/WNL.0000000000002923 27371494; PubMed Central PMCID: PMCPMC4970664.

48. O'Bryant SE, Xiao G, Barber R, Cullum CM, Weiner M, Hall J, et al. Molecular neuropsychology: creation of test-specific blood biomarker algorithms. Dement Geriatr Cogn Disord. 2014;37(1–2):45–57. Epub 2013/10/11. doi: 10.1159/000345605 24107792; PubMed Central PMCID: PMCPMC4400831.

49. Breiman L. Random Forests2001. 5–32 p.

50. Whitwell JL, Wiste HJ, Weigand SD, Rocca WA, Knopman DS, Roberts RO, et al. Comparison of imaging biomarkers in the Alzheimer Disease Neuroimaging Initiative and the Mayo Clinic Study of Aging. Arch Neurol. 2012;69(5):614–22. Epub 2012/07/12. doi: 10.1001/archneurol.2011.3029 22782510; PubMed Central PMCID: PMCPMC3569033.

51. Hebert LE, Weuve J, Scherr PA, Evans DA. Alzheimer disease in the United States (2010–2050) estimated using the 2010 census. Neurology. 2013;80(19):1778–83. Epub 2013/02/08. doi: 10.1212/WNL.0b013e31828726f5 23390181; PubMed Central PMCID: PMCPMC3719424.

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