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Classification and prediction of clinical Alzheimer's diagnosis based on plasma signaling proteins

Nature Medicine volume 13, pages 1359–1362 (2007)Cite this article

Abstract

A molecular test for Alzheimer's disease could lead to better treatment and therapies. We found 18 signaling proteins in blood plasma that can be used to classify blinded samples from Alzheimer's and control subjects with close to 90% accuracy and to identify patients who had mild cognitive impairment that progressed to Alzheimer's disease 2–6 years later. Biological analysis of the 18 proteins points to systemic dysregulation of hematopoiesis, immune responses, apoptosis and neuronal support in presymptomatic Alzheimer's disease.

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Figure 1: Study outline, clustering of training set, and predictor discovery.
Figure 2: Classification and prediction of clinical Alzheimer's diagnosis in subjects with Alzheimer's disease or MCI and functional analysis of the 18 predictive plasma signaling proteins.

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Acknowledgements

We are grateful to the individuals who participated in this study. We also thank W. Hueber for critical reading and helpful comments on the manuscript, and numerous unnamed staff of our institutions for their efforts in subject recruitment, diagnostic assessment and blood processing. This study was supported by the John Douglas French Alzheimer's Foundation (T.W.-C.), the Alzheimer's Association (T.W.-C.), the US National Institute on Aging (T.W.-C., AG20603; J.A.K., J.F.Q., AG08017; D.R.G., AG05131) and Satoris, Inc. We also acknowledge the support of the Veterans Administration Mental Illness Research, Education and Clinical Center and the various Alzheimer's Centers sponsored by the US National Institute on Aging.

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Author notes

  1. Sandip Ray and Markus Britschgi: These authors contributed equally to this work.

Authors and Affiliations

  1. Satoris, Inc., 2686 Middlefield Road, Suite E, Redwood City, 94063, California, USA

    Sandip Ray & Charles Herbert

  2. Department of Neurology and Neurological Sciences, Stanford University School of Medicine, 300 Pasteur Drive, Stanford, 94305-5235, California, USA

    Markus Britschgi, Yoshiko Takeda-Uchimura, Yuen T So & Tony Wyss-Coray

  3. Department of Neurology, Memory and Aging Center, 350 Parnassus Avenue, Suite 706, San Francisco, 94117, California, USA

    Adam Boxer, Anna Karydas, Bruce L Miller & Gil D Rabinovici

  4. Department of Experimental Neuroscience, Institute of Clinical Neuroscience, Sahlgrenska University Hospital, University of Göteborg, Blå stråket 15, Mölndal, 431 80, Sweden

    Kaj Blennow

  5. Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 300 Pasteur Drive, Stanford, 94305-5550, California, USA

    Leah F Friedman, Jared Tinklenberg & Jerome A Yesavage

  6. Department of Neurosciences, University of California, San Diego, 9500 Gilman Drive #9127, La Jolla, 92093-9127, California, USA

    Douglas R Galasko

  7. Department of Internal Medicine and Allergology, Wroclaw Medical University, Traugutta, Wroclaw, 57, 50-417, Poland

    Marek Jutel

  8. Layton Aging & Alzheimer's Disease Center, Oregon Health Sciences University, 3181 Southwest Sam Jackson Park Road, CR131, Portland, 97201-3098, Oregon, USA

    Jeffrey A Kaye & Joseph F Quinn

  9. Department of Psychiatry, Wroclaw Medical University, Pasteura, 10, 51-622, Wroclaw, Poland

    Jerzy Leszek

  10. Department of Clinical Sciences Malmö, Clinical Memory Research Unit, Lund University, Universitetssjukhuset MAS, Ingång 56 plan 7, Malmö, SE-205 02, Sweden

    Lennart Minthon

  11. Division of Immunology and Rheumatology, Stanford University School of Medicine, 300 Pasteur Drive, Stanford, 94305-5166, California, USA

    William H Robinson

  12. Sun Health Research Institute, 10515 West Santa Fe Drive, Sun City, 85351, Arizona, USA

    Marwan N Sabbagh & D Larry Sparks

  13. Department of Neurosciences, Ophthalmology, and Genetics, University of Genoa, Via A. De Toni 5, Genoa, 16132, Italy

    Massimo Tabaton

  14. Department of Health Research and Policy, Stanford University School of Medicine, 300 Pasteur Drive, Stanford, 94305-5405, California, USA

    Robert Tibshirani

  15. Geriatric Research, Education and Clinical Center, Veterans Affairs Palo Alto Health Care System, 3801 Miranda Avenue, Palo Alto, 94304, California, USA

    Tony Wyss-Coray

Authors
  1. Sandip Ray
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  2. Markus Britschgi
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  3. Charles Herbert
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  4. Yoshiko Takeda-Uchimura
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  7. Leah F Friedman
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  14. Lennart Minthon
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  15. Joseph F Quinn
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  16. Gil D Rabinovici
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  17. William H Robinson
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  18. Marwan N Sabbagh
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  19. Yuen T So
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  20. D Larry Sparks
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  21. Massimo Tabaton
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  22. Jared Tinklenberg
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  23. Jerome A Yesavage
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  24. Robert Tibshirani
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  25. Tony Wyss-Coray
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Contributions

Experiments were coordinated by S.R., M.B. and T.W.-C. Filter array experiment was done by S.R. with the help of C.H. Cytokine antibody array experiments, cluster analysis and class prediction were done by S.R. with scientific advice from R.T. Computational analysis of functional annotations was done by M.B. and T.W.-C. Blood processing, sample preparation, ELISA, subject data collection and administration was done by M.B. with the help of Y.T.-U. Recruitment of patients and control individuals, disease assessment and blood processing in center-coordinated studies was directed or done by A.B., K.B., L.F.F. D.R.G., M.J., A.K., J.A.K, J.L., B.L.M., L.M., J.F.Q., G.D.R., W.H.R., M.N.S., Y.T.S., D.L.S., M.T., J.T. and J.A.Y. The project was conceived by S.R. and T.W.-C. and scientifically directed by T.W.-C., and the paper written by M.B., T.W.-C. and S.R.

Corresponding author

Correspondence to Tony Wyss-Coray.

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Competing interests

Sandip Ray and Charles Herbert are employees of Satoris, Inc. Robert Tibshirani is a consultant for Satoris, Inc. Tony Wyss-Coray is a co-founder and consultant of Satoris, Inc.

Supplementary information

Supplementary Text and Figures

Supplementary Methods, Supplementary References, Supplementary Figs. 1–4, Supplementary Tables 1–3 (PDF 1350 kb)

Supplementary Data

Data sets (XLS 589 kb)

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Ray, S., Britschgi, M., Herbert, C. et al. Classification and prediction of clinical Alzheimer's diagnosis based on plasma signaling proteins. Nat Med 13, 1359–1362 (2007). https://doi.org/10.1038/nm1653

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