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Alzheimer's disease biomarker discovery using SOMAscan multiplexed protein technology
Open accessAbstract
Blood proteins and their complexes have become the focus of a great deal of interest in the context of their potential as biomarkers of Alzheimer's disease (AD). We used a SOMAscan assay for quantifying 1001 proteins in blood samples from 331 AD, 211 controls, and 149 mild cognitive impaired (MCI) subjects. The strongest associations of protein levels with AD outcomes were prostate‐specific antigen complexed to α1‐antichymotrypsin (AD diagnosis), pancreatic prohormone (AD diagnosis, left entorhinal cortex atrophy, and left hippocampus atrophy), clusterin (rate of cognitive decline), and fetuin B (left entorhinal atrophy). Multivariate analysis found that a subset of 13 proteins predicted AD with an accuracy of area under the curve of 0.70. Our replication of previous findings provides further evidence that levels of these proteins in plasma are truly associated with AD. The newly identified proteins could be potential biomarkers and are worthy of further investigation.
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“novel and highly sensitive high‐throughput protein arrays, such as aptamer‐based technologies, immunobased proximity extension assays, or antibody suspension beads arrays, which can readily measure large sets of protein libraries in CSF and blood samples. 132 , 133 , 134 , 135 , 136 , 137 , 138”
From New developments of biofluid‐based biomarkers for routine diagnosis and disease trajectories in frontotemporal dementia (2022) · cites this paper as [132]
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“The coverage of proteins on the platform has taken into account proteins known to be relevant to human disease, including neurodegenerative diseases55 and cardiovascular diseases56; thus it has been widely used for biomarker discovery.”
From Genomic atlas of the proteome from brain, CSF and plasma prioritizes proteins implicated in neurological disorders (2021) · cites this paper as [55]
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“The endophenotype approach is increasingly being adopted, for example, to study blood-based biomarkers of cognitive decline [23,24], apolipoprotein E ε4 (APOE ε4) carrier status [25], brain atrophy [26,27], and hippocampal metabolism [28].”
MethodSelf-citationPetek, L. M., Rickard, A. M., Budech, C. B., Poliachik, S. L., Shaw, D., Ferguson, M. R., Tawil, R., Friedman, S. D., & Miller, D. G. (2016) · Neuromuscular Disorders · doi:10.1016/j.nmd.2016.04.012 · Cited by 53
“Sattlecker M, Kiddle SJ, Newhouse S, et al. Alzheimer’s disease biomarker discovery using SOMAscan multiplexed protein technology.”
InfluentialNarzo, A. D., Telesco, S., Brodmerkel, C. M., Argmann, C., Peters, L. A., Li, K., Kidd, B. A., Dudley, J. T., Cho, J. H., Schadt, E. E., et al. (2017) · PLoS Genetics · doi:10.1371/journal.pgen.1006565 · Cited by 51
Kiddle, S. J., Steves, C. J., Mehta, M. A., Simmons, A., Xu, X., Newhouse, S., Sattlecker, M., Ashton, N. J., Bazenet, C. E., Killick, R., et al. (2015) · Translational Psychiatry · doi:10.1038/tp.2015.78 · Cited by 51
Self-citationBlood Protein Markers of Neocortical Amyloid-β Burden: A Candidate Study Using SOMAscan Technology
Voyle, N., Baker, D., Burnham, S. C., Covin, A., Zhang, Z., Sangurdekar, D. P., Hehir, C. A. T., Bazenet, C. E., Lovestone, S., Kiddle, S. J., et al. (2015) · Journal of Alzheimer s Disease · doi:10.3233/jad-150020 · Cited by 49
Self-citationWestwood, S., Liu, B., Baird, A. L., Anand, S. N., Nevado‐Holgado, A. J., Newby, D., Pikkarainen, M., Hallikainen, M., Kuusisto, J., Streffer, J. R., et al. (2017) · Alzheimer s Research & Therapy · doi:10.1186/s13195-017-0258-6 · Cited by 50
“05) [20] to identify common proteins from the two analyses.”
BackgroundInfluentialSelf-citationPlasma proteins related to inflammatory diet predict future cognitive impairment
Duggan, M. R., Butler, L., Peng, Z., Daya, G. N., Moghekar, A., An, Y., Rapp, S. R., Hayden, K. M., Shadyab, A. H., Natale, G., et al. (2023) · Molecular Psychiatry · doi:10.1038/s41380-023-01975-7 · Cited by 54
“We note, however, that although we show CCL3 and OPG are positively associated with neurodegeneration biomarkers in two separate cohorts, other investigations have failed to find associations between plasma CCL3, OPG, and atrophy in brain regions commonly implicated in AD [74, 75].”
Probing the colorectal cancer proteome for biomarkers: Current status and perspectives
Lee, P. Y., Chin, S., Low, T. Y., & Jamal, R. (2018) · Journal of Proteomics · doi:10.1016/j.jprot.2018.06.014 · Cited by 46
Chiam, J. T. W., Dobson, R., Kiddle, S. J., & Sattlecker, M. (2014) · Journal of Alzheimer s Disease · doi:10.3233/jad-140816 · Cited by 48
Self-citationDeep molecular phenotypes link complex disorders and physiological insult to CpG methylation
Zaghlool, S. B., Mook‐Kanamori, D. O., Kader, S. A., Stephan, N., Halama, A., Engelke, R., Sarwath, H., Al‐Dous, E., Mohamoud, Y. A., Roemisch‐Margl, W., et al. (2018) · Human Molecular Genetics · doi:10.1093/hmg/ddy006 · Cited by 45
Immunocapture strategies in translational proteomics
Fredolini, C., Byström, S., Pin, E., Edfors, F., Tamburro, D., Iglesias, M. J., Månberg, A., Hong, M., Uhlén, M., Nilsson, P., et al. (2015) · Expert Review of Proteomics · doi:10.1586/14789450.2016.1111141 · Cited by 47
“[31] In addition, recombinant affinity reagents such as SOMAmers, which are short single-stranded oligonucleotides based on aptamer reagents,[32] were recently used to study Alzheimer’s disease (AD) [33] and muscular dystrophies.”
MethodMuenchhoff, J., Poljak, A., Thalamuthu, A., Gupta, V. B., Chatterjee, P., Raftery, M. J., Masters, C. L., Morris, J. C., Bateman, R. J., Fagan, A. M., et al. (2016) · Scientific Reports · doi:10.1038/srep29078 · Cited by 46
“There is mounting evidence to indicate that protein (and lipid) changes in the periphery reflect the asymptomatic, prodromal and symptomatic stages of LOAD 7–9 , but how this compares to plasma protein changes in the asymptomatic and symptomatic stages of ADAD is currently unknown.”
Tarnanas, I., Tsolaki, A., Wiederhold, M. D., Wiederhold, B. K., & Tsolaki, M. (2015) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1016/j.dadm.2015.10.005 · Cited by 46
“Determining new diagnostic criteria that incorporate biomarkers to construct models of disease progression enabled the mechanism to stage and stratify patients during the presymptomatic phase [5].”
BackgroundSelf-citationFrick, E. A., Emilsson, V., Jónmundsson, Þ., Steindorsdottir, A. E., Johnson, E. C. B., Puerta, R., Dammer, E. B., Shantaraman, A., Cano, A. C., Boada, M., et al. (2024) · Nature Aging · doi:10.1038/s43587-024-00693-1 · Cited by 47
“We found differential associations between the strata for several proteins, potentially suggesting that different pathways vary in their contribution to the development of LOAD depending on APOE-ε4 carrier status (Supplementary Note 7 and Supplementary Table 15).”
InfluentialWeighted Protein Interaction Network Analysis of Frontotemporal Dementia
Ferrari, R., Lovering, R. C., Hardy, J., Lewis, P. A., & Manzoni, C. (2016) · Journal of Proteome Research · doi:10.1021/acs.jproteome.6b00934 · Cited by 39
Tweedie, D., Karnati, H. K., Mullins, R. J., Pick, C. G., Hoffer, B. J., Goetzl, E. J., Kapogiannis, D., & Greig, N. H. (2020) · eLife · doi:10.7554/elife.55827 · Cited by 42
DeMarshall, C. A., Han, M. C., Nagele, E. P., Sarkar, A., Acharya, N. K., Godsey, G. A., Goldwaser, E. L., Kosciuk, M. C., Thayasivam, U., Belinka, B. A., et al. (2015) · Immunology Letters · doi:10.1016/j.imlet.2015.09.010 · Cited by 42
A Candidate Plasma Protein Classifier to Identify Alzheimer's Disease
Zhao, X., Lejnine, S., Spond, J., Zhang, C., Ramaraj, T. C., Holder, D., Dai, H. A., WEINER, R. S., & Laterza, O. (2014) · Journal of Alzheimer s Disease · doi:10.3233/jad-141149 · Cited by 43
Heo, G., Xu, Y., Wang, E., Ali, M., Oh, H. S., Losada, P. M., Anastasi, F., Escalante, A. G., Puerta, R., Song, S., et al. (2025) · Nature Aging · doi:10.1038/s43587-025-00872-8 · Cited by 51
“We systematically compared our results to those of six previous plasma studies, three based on SomaScan 6,14,16 and three based on Olink 15,17,18 (Supplementary Tables 11–14 and Supplementary Fig.”
Murota, A., Suzuki, K., Kassai, Y., Miyazaki, T., Morita, R., Kondo, Y., Takeshita, M., Niki, Y., Yoshimura, A., & Takeuchi, T. (2015) · Cytokine · doi:10.1016/j.cyto.2015.12.002 · Cited by 39
Nanostructured materials and nanoparticles for point of care (POC) medical biosensors
Brazaca, L. C., Ribovski, L., Janegitz, B. C., & Zucolotto, V. (2016) · Elsevier eBooks · doi:10.1016/b978-0-08-100072-4.00010-1 · Cited by 42
Dang, U. J., Ziemba, M., Clemens, P. R., Hathout, Y., Conklin, L. S., CINRG Vamorolone 002/003 Investigators, & Hoffman, E. P. (2020) · Human Molecular Genetics · doi:10.1093/hmg/ddaa132 · Cited by 39
“Statistical models have being increasingly used with biomarkers to predict onset (48), model risk prediction (44), identify highly associated biomarkers from cancer exosomes (49) and identify co-regulated groups of circulating proteins demonstrating close relationships to disease states (50).”
BackgroundCuvelliez, M., Vandewalle, V., Brunin, M., Beseme, O., Hulot, A., de Groote, P., Amouyel, P., Bauters, C., Marot, G., & Pinet, F. (2019) · Scientific Reports · doi:10.1038/s41598-019-55727-1 · Cited by 38
Flotillin is a Novel Diagnostic Blood Marker of Alzheimer’s Disease
Abdullah, M., Kimura, N., Akatsu, H., Hashizume, Y., Taslima, F., Tachita, T., Iida, S., Zou, K., Matsubara, E., & Michikawa, M. (2019) · Journal of Alzheimer s Disease · doi:10.3233/jad-190908 · Cited by 36
“These studies include the quantitation of 18 plasma signaling proteins by ELISA [24], the quantitation of 10–18 other plasma proteins by multiplex assay [25, 26] or SOMAscan assay [27], and the measurement of 10 plasma phospholipids by mass spectrometry [28].”
Ashton, N. J., Benedet, A. L., Molfetta, G. D., Pola, I., Anastasi, F., Fernández‐Lebrero, A., Puig‐Pijoan, A., Keshavan, A., Schott, J. M., Tan, K., et al. (2025) · Alzheimer s & Dementia · doi:10.1002/alz.14621 · Cited by 42
Sattlecker, M., Khondoker, M. R., Proitsi, P., Williams, S. A., Soininen, H. S., Kłoszewska, I., Mecocci, P., Tsolaki, M., Vellas, B. J., Lovestone, S., et al. (2015) · Journal of Alzheimer s Disease · doi:10.3233/jad-140669 · Cited by 35
“As we had longitudinal measures for only a subset of samples (69 controls, 37 ‘stable’ MCI patients (MCIs), 39 patients with MCI converting to AD within a year (MCIc), and 90 AD patients) cross-sectional results for the complete data set comprising protein measures for 691 subjects (211 controls, 106 MCI patients, 43…”
ResultSelf-citationWestwood, S., Baird, A. L., Hye, A., Ashton, N. J., Nevado‐Holgado, A. J., Anand, S. N., Liu, B., Newby, D., Bazenet, C. E., Kiddle, S. J., et al. (2018) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2018.00409 · Cited by 35
Self-citationANMerge: A Comprehensive and Accessible Alzheimer’s Disease Patient-Level Dataset
Birkenbihl, C. J., Westwood, S., Shi, L., Nevado‐Holgado, A. J., Westman, E., Lovestone, S., & Hofmann‐Apitius, M. (2020) · Journal of Alzheimer s Disease · doi:10.3233/jad-200948 · Cited by 36
Self-citationLopez-Silva, C., Surapaneni, A., Coresh, J., Reiser, J., Parikh, C. R., Obeid, W., Grams, M. E., & Chen, T. K. (2022) · Clinical Journal of the American Society of Nephrology · doi:10.2215/cjn.11700921 · Cited by 34
Network-driven plasma proteomics expose molecular changes in the Alzheimer’s brain
Jaeger, P. A., Lucin, K. M., Britschgi, M., Vardarajan, B. N., Huang, R.-P., Kirby, E. D., Abbey, R. J., Boeve, B. F., Boxer, A. L., Farrer, L. A., et al. (2016) · Molecular Neurodegeneration · doi:10.1186/s13024-016-0095-2 · Cited by 35
“Future developments in the production of antibodies or antibody alternatives such as aptamteres [40, 41] will likely enable researchers to probe even broader sets of circulating antigens.”
BackgroundPeña‐Bautista, C., Baquero, M., Vento, M., & Cháfer‐Pericás, C. (2018) · Current Neuropharmacology · doi:10.2174/1570159x16666180926123722 · Cited by 34
“Most of the AD diagnostic models developed in literature from omic tools were based on proteomic signatures and showed satisfactory accuracy (70-94%) [30, 38, 81, 86-89], as well as high sensitivity and specificity (74-85%) [86, 90, 91].”
BackgroundMethodGupta, V. B., Hone, E., Pedrini, S., Doecke, J. D., O’Bryant, S. E., JAMES, I. R., Bush, A. I., Rowe, C. C., Villemagne, V. L., Ames, D. J., et al. (2017) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1016/j.dadm.2017.04.003 · Cited by 36
Blood Biomarkers for Alzheimer’s Disease: Much Promise, Cautious Progress
Keshavan, A., Heslegrave, A., Zetterberg, H., & Schott, J. M. (2017) · Molecular Diagnosis & Therapy · doi:10.1007/s40291-016-0241-0 · Cited by 34
Koychev, I. G., Reid, G., Nguyen, M., Mentz, R. J., Joyce, D. W., Shah, S. H., & Holman, R. R. (2024) · Alzheimer s Research & Therapy · doi:10.1186/s13195-024-01573-x · Cited by 37
“In people across the AD spectrum, FCN2 is increased in those with lower levels of CSF phosphorylated tau [30] and larger entorhinal cortex volumes [14].”
BackgroundResultPark, Y. H., Pyun, J., Hodges, A., Jang, J., Bice, P. J., Kim, S., Saykin, A. J., & Nho, K. T. (2021) · Alzheimer s Research & Therapy · doi:10.1186/s13195-021-00919-z · Cited by 32
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Enhanced Multiplexing Technology for Proteomics
Bowser, B. L., & Robinson, R. A. S. (2023) · Annual Review of Analytical Chemistry · doi:10.1146/annurev-anchem-091622-092353 · Cited by 32
Teng, E., Chow, N., Hwang, K., Thompson, P. M., Gylys, K. H., Cole, G. M., Jack, C. R., Shaw, L. M. J., Trojanowski, J. Q., Soares, H. D., et al. (2014) · Dementia and Geriatric Cognitive Disorders · doi:10.1159/000368982 · Cited by 33
Qiao, Z., Pan, X., Parlayan, C., Ojima, H., & Kondo, T. (2016) · Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics · doi:10.1016/j.bbapap.2016.09.011 · Cited by 30
High-Throughput Identification of the Plasma Proteomic Signature of Inflammatory Bowel Disease
Narzo, A. D., Brodmerkel, C. M., Telesco, S., Argmann, C., Peters, L. A., Li, K., Kidd, B. A., Dudley, J. T., Cho, J. H., Schadt, E. E., et al. (2018) · Journal of Crohn s and Colitis · doi:10.1093/ecco-jcc/jjy190 · Cited by 30
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Gu, J., Wang, L., Zhao, L., Zuo, Y., Gao, S., Gu, H., Wang, Y., & Yu, Y. (2024) · Sensors and Actuators B Chemical · doi:10.1016/j.snb.2024.135456 · Cited by 29
Metadata
- Authors
- Sattlecker, M., Kiddle, S. J., Newhouse, S., Proitsi, P., Nelson, S., Williams, S., Johnston, C., Killick, R., Simmons, A., Westman, E., Hodges, A., Soininen, H., Kłoszewska, I., Mecocci, P., Tsolaki, M., Vellas, B., Lovestone, S., AddNeuroMed Consortium, & Dobson, R. J. B.
- Affiliations
- King's College London (GB)
- SomaLogic (United States) (US)
- University of Eastern Finland (FI)
- Medical University of Lodz (PL)
- University of Perugia (IT)
- Aristotle University of Thessaloniki (GR)
- Inserm (FR)
- Corresponding author
- Dobson, Richard J.B.
- ORCID
- Venue
- Alzheimer's & Dementia
- Publisher
- Wiley
- Published
- 2014-04-28
- Volume
- 10
- Issue
- 6
- Pages
- 724-734
- ISSN
- 1552-5260 (ISSN-L)
- 1552-5279
- OpenAlex
- W2035892094
- Cited by
- 223
- References
- 54
- Citations by year
- 2026: 7 · 2025: 19 · 2024: 19 · 2023: 15 · 2022: 13 · 2021: 26 · 2020: 22 · 2019: 16 · 2018: 18 · 2017: 13 · 2016: 20 · 2015: 26 · 2014: 9
- FWCI
- 17.31
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Alzheimer s & Dementia (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Research Portal (King's College London) (acceptedVersion, cc-by-nc-nd)
- UCL Discovery (University College London) (submittedVersion)
- INFM-OAR (INFN Catania) (submittedVersion, cc-by-nc-nd)
- Funders
- NIHR Newcastle Biomedical Research Centre
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
- Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
- Keywords
- Alzheimer's disease, biomarkers
- MeSH terms
- Aged, Aged, 80 and over, Alzheimer Disease, Atrophy, Blood Proteins, Brain, Female, Humans, Magnetic Resonance Imaging, Male, ROC Curve, Cohort Studies, Biomarkers, Logistic Models, Proteomics, Cognitive Dysfunction
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