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Diagnostic amyloid proteomics: experience of the UK National Amyloidosis Centre

  • Diana Canetti EMAIL logo , Nigel B. Rendell , Janet A. Gilbertson , Nicola Botcher , Paola Nocerino , Angel Blanco , Lucia Di Vagno , Dorota Rowczenio , Guglielmo Verona , P. Patrizia Mangione , Vittorio Bellotti , Philip N. Hawkins , Julian D. Gillmore and Graham W. Taylor
Published/Copyright: February 18, 2020

Abstract

Systemic amyloidosis is a serious disease which is caused when normal circulating proteins misfold and aggregate extracellularly as insoluble fibrillary deposits throughout the body. This commonly results in cardiac, renal and neurological damage. The tissue target, progression and outcome of the disease depends on the type of protein forming the fibril deposit, and its correct identification is central to determining therapy. Proteomics is now used routinely in our centre to type amyloid; over the past 7 years we have examined over 2000 clinical samples. Proteomics results are linked directly to our patient database using a simple algorithm to automatically highlight the most likely amyloidogenic protein. Whilst the approach has proved very successful, we have encountered a number of challenges, including poor sample recovery, limited enzymatic digestion, the presence of multiple amyloidogenic proteins and the identification of pathogenic variants. Our proteomics procedures and approaches to resolving difficult issues are outlined.


Corresponding author: Dr. Diana Canetti, Wolfson Drug Discovery Unit and National Amyloidosis Centre, Centre for Amyloidosis and Acute Phase Proteins, Division of Medicine, University College London, Royal Free Campus, Rowland Hill Street, London NW3 2PF, UK, Phone: +44 (0)207 433 2824

  1. Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: The UK National Amyloidosis Centre is funded by NHS England. Core support for the Wolfson Drug Discovery Unit is provided by the UK National Institute for Health Research Biomedical Research Centre and Unit Funding scheme via the UCLH/UCL Biomedical Research Centre. Funding for the proteomics platform was generously provided by the Wolfson Foundation, Funder Id: http://dx.doi.org/10.13039/501100001320, Grant Number: PR/YLR/NW/20885 and the UCL Amyloidosis Research Fund.

  3. Employment or leadership: None declared.

  4. Honorarium: None declared.

  5. Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.

  6. Ethical approval: All patients were managed in accordance with the Declaration of Helsinki and informed consent for use of material and publication of data was obtained.

References

1. Pepys MB. Amyloidosis. Annu Rev Med 2006;57:223–41.10.1146/annurev.med.57.121304.131243Search in Google Scholar

2. Benson MD, Buxbaum JN, Eisenberg DS, Merlini G, Saraiva MJ, Sekijima Y, et al. Amyloid nomenclature 2018: recommendations by the International Society of Amyloidosis (ISA) nomenclature committee. Amyloid 2018;25:215–9.10.1080/13506129.2018.1549825Search in Google Scholar

3. Pinney JH, Whelan CJ, Petrie A, Dungu J, Banypersad SM, Sattianayagam P, et al. Senile systemic amyloidosis: clinical features at presentation and outcome. J Am Heart Assoc 2013;2:e000098.10.1161/JAHA.113.000098Search in Google Scholar

4. Westermark GT, Fandrich M, Westermark P. AA amyloidosis: pathogenesis and targeted therapy. Annu Rev Pathol 2015;10:321–44.10.1146/annurev-pathol-020712-163913Search in Google Scholar

5. Puchtler H, Waldrop FS, Meloan SN. A review of light, polarization and fluorescence microscopic methods for amyloid. Appl Pathol 1985;3:5–17.Search in Google Scholar

6. Pras M, Schubert M, Zucker-Franklin D, Rimon A, Franklin EC. The characterization of soluble amyloid prepared in water. J Clin Invest 1968;47:924–33.10.1172/JCI105784Search in Google Scholar

7. Tennent GA. Isolation and characterization of amyloid fibrils from tissue. Methods Enzymol 1999;309:26–47.10.1016/S0076-6879(99)09004-7Search in Google Scholar

8. Tveteraas T, Sletten K, Westermark P. The amino acid sequence of a carbohydrate-containing immunoglobulin-light-chain-type amyloid-fibril protein. Biochem J 1985;232:183–90.10.1042/bj2320183Search in Google Scholar

9. Nichols WC, Dwulet FE, Liepnieks J, Benson MD. Variant apolipoprotein AI as a major constituent of a human hereditary amyloid. Biochem Biophys Res Commun 1988;156:762–8.10.1016/S0006-291X(88)80909-4Search in Google Scholar

10. Linke RP. On typing amyloidosis using immunohistochemistry. Detailed illustrations, review and a note on mass spectrometry. Prog Histochem Cytochem 2012;47:61–132.10.1016/j.proghi.2012.03.001Search in Google Scholar PubMed

11. Gilbertson JA, Hunt T, Hawkins PN. Amyloid typing: experience from a large referral centre. In: Picken M, Dogan A, Herrera G, editors. Amyloid and related disorders current clinical pathology. NJ, USA: Humana Press, 2012:231–8.10.1007/978-1-60761-389-3_18Search in Google Scholar

12. Liao L, Cheng D, Wang J, Duong DM, Losik TG, Gearing M, et al. Proteomic characterization of postmortem amyloid plaques isolated by laser capture microdissection. J Biol Chem 2004;279:37061–8.10.1074/jbc.M403672200Search in Google Scholar PubMed

13. Palmer-Toy DE, Krastins B, Sarracino DA, Nadol Jr JB, Merchant SN. Efficient method for the proteomic analysis of fixed and embedded tissues. J Proteome Res 2005;4:2404–11.10.1021/pr050208pSearch in Google Scholar PubMed

14. Hood BL, Conrads TP, Veenstra TD. Mass spectrometric analysis of formalin-fixed paraffin-embedded tissue: unlocking the proteome within. Proteomics 2006;6:4106–14.10.1002/pmic.200600016Search in Google Scholar PubMed

15. Emmert-Buck MR, Bonner RF, Smith PD, Chuaqui RF, Zhuang Z, Goldstein SR, et al. Laser capture microdissection. Science 1996;274:998–1001.10.1126/science.274.5289.998Search in Google Scholar PubMed

16. Rodriguez FJ, Gamez JD, Vrana JA, Theis JD, Giannini C, Scheithauer BW, et al. Immunoglobulin derived depositions in the nervous system: novel mass spectrometry application for protein characterization in formalin-fixed tissues. Lab Invest 2008;88:1024–37.10.1038/labinvest.2008.72Search in Google Scholar PubMed

17. Vrana JA, Gamez JD, Madden BJ, Theis JD, Bergen 3rd HR, Dogan A. Classification of amyloidosis by laser microdissection and mass spectrometry-based proteomic analysis in clinical biopsy specimens. Blood 2009;114:4957–9.10.1182/blood-2009-07-230722Search in Google Scholar PubMed

18. Sethi S, Vrana JA, Theis JD, Leung N, Sethi A, Nasr SH, et al. Laser microdissection and mass spectrometry-based proteomics aids the diagnosis and typing of renal amyloidosis. Kidney Int 2012;82:226–34.10.1038/ki.2012.108Search in Google Scholar PubMed PubMed Central

19. Dogan A. Amyloidosis: insights from proteomics. Annu Rev Pathol 2017;12:277–304.10.1146/annurev-pathol-052016-100200Search in Google Scholar PubMed

20. Tennent GA, Cafferty KD, Pepys MB, Hawkins PN. Congo red overlay immunohistochemistry aids classification of amyloid deposits. In: Kyle RA, Gertz MA, editors. Amyloid and Amyloidosis, 1998. Pearl River, New York: Parthenon Publishing, 1999:160–2.Search in Google Scholar

21. Rezk T, Gilbertson JA, Mangione PP, Rowczenio D, Rendell NB, Canetti D, et al. The complementary role of histology and proteomics for diagnosis and typing of systemic amyloidosis. J Pathol Clin Res 2019;5:145–53.10.1002/cjp2.126Search in Google Scholar PubMed PubMed Central

22. Fang J, Rand KD, Beuning PJ, Engen JR. False EX1 signatures caused by sample carryover during HX MS analyses. Int J Mass Spectrom 2011;302:19–25.10.1016/j.ijms.2010.06.039Search in Google Scholar PubMed PubMed Central

23. Shteynberg D, Nesvizhskii AI, Moritz RL, Deutsch EW. Combining results of multiple search engines in proteomics. Mol Cell Proteomics 2013;12:2383–93.10.1074/mcp.R113.027797Search in Google Scholar

24. Yuan ZF, Lin S, Molden RC, Garcia BA. Evaluation of proteomic search engines for the analysis of histone modifications. J Proteome Res 2014;13:4470–8.10.1021/pr5008015Search in Google Scholar

25. Dasari S, Amin MS, Kurtin PJ, Vrana JA, Theis JD, Grogg KL, et al. Clinical, biopsy, and mass spectrometry characteristics of renal apolipoprotein A-IV amyloidosis. Kidney Int 2016;90:658–64.10.1016/j.kint.2016.04.003Search in Google Scholar

26. Theis JD, Dasari S, Vrana JA, Kurtin PJ, Dogan A. Shotgun- proteomics-based clinical testing for diagnosis and classification of amyloidosis. J Mass Spectrom 2013;48: 1067–77.10.1002/jms.3264Search in Google Scholar

27. Dasari S, Theis JD, Vrana JA, Zenka RM, Zimmermann MT, Kocher JP, et al. Clinical proteome informatics workbench detects pathogenic mutations in hereditary amyloidoses. J Proteome Res 2014;13:2352–8.10.1021/pr4011475Search in Google Scholar

28. Winter M, Tholey A, Kruger S, Schmidt H, Rocken C. MALDI-mass spectrometry imaging identifies vitronectin as a common constituent of amyloid deposits. J Histochem Cytochem 2015;63:772–9.10.1369/0022155415595264Search in Google Scholar

29. Mollee P, Boros S, Loo D, Ruelcke JE, Lakis VA, Cao KL, et al. Implementation and evaluation of amyloidosis subtyping by laser-capture microdissection and tandem mass spectrometry. Clin Proteomics 2016;13:30.10.1186/s12014-016-9133-xSearch in Google Scholar

30. Yamagoe S, Yamakawa Y, Matsuo Y, Minowada J, Mizuno S, Suzuki K. Purification and primary amino acid sequence of a novel neutrophil chemotactic factor LECT2. Immunol Lett 1996;52:9–13.10.1016/0165-2478(96)02572-2Search in Google Scholar

31. Benson MD, James S, Scott K, Liepnieks JJ, Kluve-Beckerman B. Leukocyte chemotactic factor 2: a novel renal amyloid protein. Kidney Int 2008;74:218–22.10.1038/ki.2008.152Search in Google Scholar PubMed

32. Rezk T, Gilbertson JA, Rowczenio D, Bass P, Lachmann HJ, Wechalekar AD, et al. Diagnosis, pathogenesis and outcome in leucocyte chemotactic factor 2 (ALECT2) amyloidosis. Nephrol Dial Transplant 2018;33:241–7.10.1093/ndt/gfw375Search in Google Scholar PubMed

33. Soutar AK, Hawkins PN, Vigushin DM, Tennent GA, Booth SE, Hutton T, et al. Apolipoprotein AI mutation Arg-60 causes autosomal dominant amyloidosis. Proc Natl Acad Sci U S A 1992;89:7389–93.10.1073/pnas.89.16.7389Search in Google Scholar PubMed PubMed Central

34. Bois MC, Dasari S, Mills JR, Theis J, Highsmith WE, Vrana JA, et al. Apolipoprotein A-IV-associated cardiac amyloidosis. J Am Coll Cardiol 2017;69:2248–9.10.1016/j.jacc.2017.02.047Search in Google Scholar PubMed

35. Bergstrom J, Murphy CL, Weiss DT, Solomon A, Sletten K, Hellman U, et al. Two different types of amyloid deposits–apolipoprotein A-IV and transthyretin – in a patient with systemic amyloidosis. Lab Invest 2004;84:981–8.10.1038/labinvest.3700124Search in Google Scholar PubMed

36. Solomon A, Weiss DT, Murphy C. Primary amyloidosis associated with a novel heavy-chain fragment (AH amyloidosis). Am J Hematol 1994;45:171–6.10.1002/ajh.2830450214Search in Google Scholar PubMed

37. Sethi S, Theis JD, Leung N, Dispenzieri A, Nasr SH, Fidler ME, et al. Mass spectrometry-based proteomic diagnosis of renal immunoglobulin heavy chain amyloidosis. Clin J Am Soc Nephrol 2010;5:2180–7.10.2215/CJN.02890310Search in Google Scholar PubMed PubMed Central

38. Picken MM. Non-light-chain immunoglobulin amyloidosis: time to expand or refine the spectrum to include light+heavy chain amyloidosis? Kidney Int 2013;83:353–6.10.1038/ki.2012.433Search in Google Scholar PubMed

39. Nasr SH, Said SM, Valeri AM, Sethi S, Fidler ME, Cornell LD, et al. The diagnosis and characteristics of renal heavy-chain and heavy/light-chain amyloidosis and their comparison with renal light-chain amyloidosis. Kidney Int 2013;83:463–70.10.1038/ki.2012.414Search in Google Scholar PubMed

40. Nasr SH, Vrana JA, Dasari S, Bridoux F, Fidler ME, Kaaki S, et al. DNAJB9 is a specific immunohistochemical marker for fibrillary glomerulonephritis. Kidney Int Rep 2018;3:56–64.10.1016/j.ekir.2017.07.017Search in Google Scholar PubMed PubMed Central

41. Ganeval D, Noel LH, Preud’homme JL, Droz D, Grunfeld JP. Light-chain deposition disease: its relation with AL-type amyloidosis. Kidney Int 1984;26:1–9.10.1038/ki.1984.126Search in Google Scholar PubMed

42. Gallo G, Picken M, Frangione B, Buxbaum J. Nonamyloidotic monoclonal immunoglobulin deposits lack amyloid P component. Mod Pathol 1988;1:453–6.Search in Google Scholar

43. Mahmood S, Gilbertson JA, Rendell N, Whelan CJ, Lachmann HJ, Wechalekar AD, et al. Two types of amyloid in a single heart. Blood 2014;124:3025–7.10.1182/blood-2014-06-580720Search in Google Scholar PubMed PubMed Central

44. Godecke VA, Rocken C, Steinmuller-Magin L, Nadrowitz F, Fleig SV, Haller H, et al. Mixed leukocyte cell-derived chemotaxin 2 and amyloid A renal amyloidosis in a Kazakh-German patient. Clin Kidney J 2017;10:266–8.10.1093/ckj/sfw147Search in Google Scholar

45. Sidiqi MH, McPhail ED, Theis JD, Dasari S, Vrana JA, Drosou ME, et al. Two types of amyloidosis presenting in a single patient: a case series. Blood Cancer J 2019;9:30.10.1038/s41408-019-0193-9Search in Google Scholar

46. Cornwell 3rd GG, Murdoch WL, Kyle RA, Westermark P, Pitkanen P. Frequency and distribution of senile cardiovascular amyloid. A clinicopathologic correlation. Am J Med 1983;75:618–23.10.1016/0002-9343(83)90443-6Search in Google Scholar

47. Tanskanen M, Peuralinna T, Polvikoski T, Notkola IL, Sulkava R, Hardy J, et al. Senile systemic amyloidosis affects 25% of the very aged and associates with genetic variation in alpha2-macroglobulin and tau: a population-based autopsy study. Ann Med 2008;40:232–9.10.1080/07853890701842988Search in Google Scholar PubMed

48. Taylor GW, Gilbertson JA, Sayed R, Blanco A, Rendell NB, Rowczenio D, et al. Proteomic analysis for the diagnosis of fibrinogen aalpha-chain amyloidosis. Kidney Int Rep 2019;4:977–86.10.1016/j.ekir.2019.04.007Search in Google Scholar PubMed PubMed Central

49. Mazza G, Simons JP, Al-Shawi R, Ellmerich S, Urbani L, Giorgetti S, et al. Amyloid persistence in decellularized liver: biochemical and histopathological characterization. Amyloid 2016;23:1–7.10.3109/13506129.2015.1110518Search in Google Scholar PubMed PubMed Central

50. Mangione PP, Mazza G, Gilbertson JA, Rendell NB, Canetti D, Giorgetti S, et al. Increasing the accuracy of proteomic typing by decellularisation of amyloid tissue biopsies. J Proteomics 2017;165:113–8.10.1016/j.jprot.2017.06.016Search in Google Scholar PubMed PubMed Central

51. Gillmore JD, Lachmann HJ, Rowczenio D, Gilbertson JA, Zeng CH, Liu ZH, et al. Diagnosis, pathogenesis, treatment, and prognosis of hereditary fibrinogen A alpha-chain amyloidosis. J Am Soc Nephrol 2009;20:444–51.10.1681/ASN.2008060614Search in Google Scholar PubMed PubMed Central

52. Benson MD, Liepnieks J, Uemichi T, Wheeler G, Correa R. Hereditary renal amyloidosis associated with a mutant fibrinogen alpha-chain. Nat Genet 1993;3:252–5.10.1038/ng0393-252Search in Google Scholar PubMed

53. Pepys MB, Hawkins PN, Booth DR, Vigushin DM, Tennent GA, Soutar AK, et al. Human lysozyme gene mutations cause hereditary systemic amyloidosis. Nature 1993;362:553–7.10.1038/362553a0Search in Google Scholar PubMed

54. Saraiva MJ, Birken S, Costa PP, Goodman DS. Amyloid fibril protein in familial amyloidotic polyneuropathy, Portuguese type. Definition of molecular abnormality in transthyretin (prealbumin). J Clin Invest 1984;74:104–19.10.1172/JCI111390Search in Google Scholar

55. Jacobson DR, Gorevic PD, Buxbaum JN. A homozygous transthyretin variant associated with senile systemic amyloidosis: evidence for a late-onset disease of genetic etiology. Am J Hum Genet 1990;47:127–36.Search in Google Scholar

56. Rowczenio DM, Noor I, Gillmore JD, Lachmann HJ, Whelan C, Hawkins PN, et al. Online registry for mutations in hereditary amyloidosis including nomenclature recommendations. Hum Mutat 2014;35:E2403–12.10.1002/humu.22619Search in Google Scholar

57. Rowczenio D, Stensland M, de Souza GA, Strom EH, Gilbertson JA, Taylor G, et al. Renal amyloidosis associated with 5 novel variants in the fibrinogen A alpha chain protein. Kidney Int Rep 2017;2:461–9.10.1016/j.ekir.2016.11.005Search in Google Scholar

58. Garnier C, Briki F, Nedelec B, Le Pogamp P, Dogan A, Rioux-Leclercq N, et al. VLITL is a major cross-beta-sheet signal for fibrinogen Aalpha-chain frameshift variants. Blood 2017;130:2799–807.10.1182/blood-2017-07-796185Search in Google Scholar

59. Bergstrom J, Gustavsson A, Hellman U, Sletten K, Murphy CL, Weiss DT, et al. Amyloid deposits in transthyretin-derived amyloidosis: cleaved transthyretin is associated with distinct amyloid morphology. J Pathol 2005;206:224–32.10.1002/path.1759Search in Google Scholar

60. Marcoux J, Mangione PP, Porcari R, Degiacomi MT, Verona G, Taylor GW, et al. A novel mechano-enzymatic cleavage mechanism underlies transthyretin amyloidogenesis. EMBO Mol Med 2015;7:1337–49.10.15252/emmm.201505357Search in Google Scholar

61. Canetti D, Rendell NB, Di Vagno L, Gilbertson JA, Rowczenio D, Rezk T, et al. Misidentification of transthyretin and immunoglobulin variants by proteomics due to methyl lysine formation in formalin-fixed paraffin-embedded amyloid tissue. Amyloid 2017;24:233–41.10.1080/13506129.2017.1385452Search in Google Scholar

62. Wu TT, Kabat EA. An analysis of the sequences of the variable regions of Bence Jones proteins and myeloma light chains and their implications for antibody complementarity. J Exp Med 1970;132:211–50.10.1084/jem.132.2.211Search in Google Scholar

63. Martin AC. Accessing the Kabat antibody sequence database by computer. Proteins 1996;25:130–3.10.1002/(SICI)1097-0134(199605)25:1<130::AID-PROT11>3.0.CO;2-LSearch in Google Scholar

64. Dasari S, Theis JD, Vrana JA, Meureta OM, Quint PS, Muppa P, et al. Proteomic detection of immunoglobulin light chain variable region peptides from amyloidosis patient biopsies. J Proteome Res 2015;14:1957–67.10.1021/acs.jproteome.5b00015Search in Google Scholar

65. Bodi K, Prokaeva T, Spencer B, Eberhard M, Connors LH, Seldin DC. AL-Base: a visual platform analysis tool for the study of amyloidogenic immunoglobulin light chain sequences. Amyloid 2009;16:1–8.10.1080/13506120802676781Search in Google Scholar PubMed PubMed Central

66. Gilbertson JA, Theis JD, Vrana JA, Lachmann H, Wechalekar A, Whelan C, et al. A comparison of immunohistochemistry and mass spectrometry for determining the amyloid fibril protein from formalin-fixed biopsy tissue. J Clin Pathol 2015;68:314–7.10.1136/jclinpath-2014-202722Search in Google Scholar PubMed


Supplementary Material

The online version of this article offers supplementary material (https://doi.org/10.1515/cclm-2019-1007).


Received: 2019-09-30
Accepted: 2020-01-16
Published Online: 2020-02-18
Published in Print: 2020-06-25

©2020 Walter de Gruyter GmbH, Berlin/Boston

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