Plasma based markers of [11C] PiB-PET brain amyloid burden

Steven John Kiddle; Madhav Thambisetty; Andrew Simmons; Joanna Riddoch-Contreras; Abdul Hye; Eric Westman; Ian Pike; Malcolm Ward; Caroline Johnston; Michelle Katharine Lupton; Katie Lunnon; Hilkka Soininen; Iwona Kloszewska; Magda Tsolaki; Bruno Vellas; Patrizia Mecocci; Simon Lovestone; Stephen Newhouse; Richard Dobson

doi:10.1371/journal.pone.0044260

Plasma based markers of [11C] PiB-PET brain amyloid burden

Steven John Kiddle, Madhav Thambisetty, Andrew Simmons, Joanna Riddoch-Contreras, Abdul Hye, Eric Westman, Ian Pike, Malcolm Ward, Caroline Johnston, Michelle Katharine Lupton, Katie Lunnon, Hilkka Soininen, Iwona Kloszewska, Magda Tsolaki, Bruno Vellas, Patrizia Mecocci, Simon Lovestone, Stephen Newhouse, Richard Dobson

Research output: Contribution to journal › Article › peer-review

82 Citations (Scopus)

Abstract

Changes in brain amyloid burden have been shown to relate to Alzheimer's disease pathology, and are believed to precede the development of cognitive decline. There is thus a need for inexpensive and non-invasive screening methods that are able to accurately estimate brain amyloid burden as a marker of Alzheimer's disease. One potential method would involve using demographic information and measurements on plasma samples to establish biomarkers of brain amyloid burden; in this study data from the Alzheimer's Disease Neuroimaging Initiative was used to explore this possibility. Sixteen of the analytes on the Rules Based Medicine Human Discovery Multi-Analyte Profile 1.0 panel were found to associate with [11C]-PiB PET measurements. Some of these markers of brain amyloid burden were also found to associate with other AD related phenotypes. Thirteen of these markers of brain amyloid burden – c-peptide, fibrinogen, alpha-1-antitrypsin, pancreatic polypeptide, complement C3, vitronectin, cortisol, AXL receptor kinase, interleukin-3, interleukin-13, matrix metalloproteinase-9 total, apolipoprotein E and immunoglobulin E – were used along with co-variates in multiple linear regression, and were shown by cross-validation to explain >30% of the variance of brain amyloid burden. When a threshold was used to classify subjects as PiB positive, the regression model was found to predict actual PiB positive individuals with a sensitivity of 0.918 and a specificity of 0.545. The number of APOE ϵ 4 alleles and plasma apolipoprotein E level were found to contribute most to this model, and the relationship between these variables and brain amyloid burden was explored.

Original language	English
Article number	e44260
Number of pages	10
Journal	PL o S One
Volume	7
Issue number	9
DOIs	https://doi.org/10.1371/journal.pone.0044260
Publication status	Published - 24 Sept 2012

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1371/journal.pone.0044260

Cite this

Kiddle, S. J., Thambisetty, M., Simmons, A., Riddoch-Contreras, J., Hye, A., Westman, E., Pike, I., Ward, M., Johnston, C., Lupton, M. K., Lunnon, K., Soininen, H., Kloszewska, I., Tsolaki, M., Vellas, B., Mecocci, P., Lovestone, S., Newhouse, S., & Dobson, R. (2012). Plasma based markers of [11C] PiB-PET brain amyloid burden. PL o S One , 7(9), Article e44260. https://doi.org/10.1371/journal.pone.0044260

@article{89a8bc1c728d4d8086cfc1994d7a64e0,

title = "Plasma based markers of [11C] PiB-PET brain amyloid burden",

abstract = "Changes in brain amyloid burden have been shown to relate to Alzheimer's disease pathology, and are believed to precede the development of cognitive decline. There is thus a need for inexpensive and non-invasive screening methods that are able to accurately estimate brain amyloid burden as a marker of Alzheimer's disease. One potential method would involve using demographic information and measurements on plasma samples to establish biomarkers of brain amyloid burden; in this study data from the Alzheimer's Disease Neuroimaging Initiative was used to explore this possibility. Sixteen of the analytes on the Rules Based Medicine Human Discovery Multi-Analyte Profile 1.0 panel were found to associate with [11C]-PiB PET measurements. Some of these markers of brain amyloid burden were also found to associate with other AD related phenotypes. Thirteen of these markers of brain amyloid burden – c-peptide, fibrinogen, alpha-1-antitrypsin, pancreatic polypeptide, complement C3, vitronectin, cortisol, AXL receptor kinase, interleukin-3, interleukin-13, matrix metalloproteinase-9 total, apolipoprotein E and immunoglobulin E – were used along with co-variates in multiple linear regression, and were shown by cross-validation to explain >30% of the variance of brain amyloid burden. When a threshold was used to classify subjects as PiB positive, the regression model was found to predict actual PiB positive individuals with a sensitivity of 0.918 and a specificity of 0.545. The number of APOE ϵ 4 alleles and plasma apolipoprotein E level were found to contribute most to this model, and the relationship between these variables and brain amyloid burden was explored.",

author = "Kiddle, {Steven John} and Madhav Thambisetty and Andrew Simmons and Joanna Riddoch-Contreras and Abdul Hye and Eric Westman and Ian Pike and Malcolm Ward and Caroline Johnston and Lupton, {Michelle Katharine} and Katie Lunnon and Hilkka Soininen and Iwona Kloszewska and Magda Tsolaki and Bruno Vellas and Patrizia Mecocci and Simon Lovestone and Stephen Newhouse and Richard Dobson",

year = "2012",

month = sep,

day = "24",

doi = "10.1371/journal.pone.0044260",

language = "English",

volume = "7",

journal = "PL o S One ",

issn = "1932-6203",

publisher = "Public Library of Science",

number = "9",

}

Kiddle, SJ , Thambisetty, M , Simmons, A , Riddoch-Contreras, J , Hye, A, Westman, E, Pike, I, Ward, M, Johnston, C, Lupton, MK , Lunnon, K, Soininen, H, Kloszewska, I, Tsolaki, M, Vellas, B, Mecocci, P, Lovestone, S , Newhouse, S & Dobson, R 2012, 'Plasma based markers of [11C] PiB-PET brain amyloid burden', PL o S One , vol. 7, no. 9, e44260. https://doi.org/10.1371/journal.pone.0044260

TY - JOUR

T1 - Plasma based markers of [11C] PiB-PET brain amyloid burden

AU - Kiddle, Steven John

AU - Thambisetty, Madhav

AU - Simmons, Andrew

AU - Riddoch-Contreras, Joanna

AU - Hye, Abdul

AU - Westman, Eric

AU - Pike, Ian

AU - Ward, Malcolm

AU - Johnston, Caroline

AU - Lupton, Michelle Katharine

AU - Lunnon, Katie

AU - Soininen, Hilkka

AU - Kloszewska, Iwona

AU - Tsolaki, Magda

AU - Vellas, Bruno

AU - Mecocci, Patrizia

AU - Lovestone, Simon

AU - Newhouse, Stephen

AU - Dobson, Richard

PY - 2012/9/24

Y1 - 2012/9/24

N2 - Changes in brain amyloid burden have been shown to relate to Alzheimer's disease pathology, and are believed to precede the development of cognitive decline. There is thus a need for inexpensive and non-invasive screening methods that are able to accurately estimate brain amyloid burden as a marker of Alzheimer's disease. One potential method would involve using demographic information and measurements on plasma samples to establish biomarkers of brain amyloid burden; in this study data from the Alzheimer's Disease Neuroimaging Initiative was used to explore this possibility. Sixteen of the analytes on the Rules Based Medicine Human Discovery Multi-Analyte Profile 1.0 panel were found to associate with [11C]-PiB PET measurements. Some of these markers of brain amyloid burden were also found to associate with other AD related phenotypes. Thirteen of these markers of brain amyloid burden – c-peptide, fibrinogen, alpha-1-antitrypsin, pancreatic polypeptide, complement C3, vitronectin, cortisol, AXL receptor kinase, interleukin-3, interleukin-13, matrix metalloproteinase-9 total, apolipoprotein E and immunoglobulin E – were used along with co-variates in multiple linear regression, and were shown by cross-validation to explain >30% of the variance of brain amyloid burden. When a threshold was used to classify subjects as PiB positive, the regression model was found to predict actual PiB positive individuals with a sensitivity of 0.918 and a specificity of 0.545. The number of APOE ϵ 4 alleles and plasma apolipoprotein E level were found to contribute most to this model, and the relationship between these variables and brain amyloid burden was explored.

AB - Changes in brain amyloid burden have been shown to relate to Alzheimer's disease pathology, and are believed to precede the development of cognitive decline. There is thus a need for inexpensive and non-invasive screening methods that are able to accurately estimate brain amyloid burden as a marker of Alzheimer's disease. One potential method would involve using demographic information and measurements on plasma samples to establish biomarkers of brain amyloid burden; in this study data from the Alzheimer's Disease Neuroimaging Initiative was used to explore this possibility. Sixteen of the analytes on the Rules Based Medicine Human Discovery Multi-Analyte Profile 1.0 panel were found to associate with [11C]-PiB PET measurements. Some of these markers of brain amyloid burden were also found to associate with other AD related phenotypes. Thirteen of these markers of brain amyloid burden – c-peptide, fibrinogen, alpha-1-antitrypsin, pancreatic polypeptide, complement C3, vitronectin, cortisol, AXL receptor kinase, interleukin-3, interleukin-13, matrix metalloproteinase-9 total, apolipoprotein E and immunoglobulin E – were used along with co-variates in multiple linear regression, and were shown by cross-validation to explain >30% of the variance of brain amyloid burden. When a threshold was used to classify subjects as PiB positive, the regression model was found to predict actual PiB positive individuals with a sensitivity of 0.918 and a specificity of 0.545. The number of APOE ϵ 4 alleles and plasma apolipoprotein E level were found to contribute most to this model, and the relationship between these variables and brain amyloid burden was explored.

U2 - 10.1371/journal.pone.0044260

DO - 10.1371/journal.pone.0044260

M3 - Article

C2 - 23028511

SN - 1932-6203

VL - 7

JO - PL o S One

JF - PL o S One

IS - 9

M1 - e44260

ER -

Plasma based markers of [11C] PiB-PET brain amyloid burden

Abstract

UN SDGs

Access to Document

Fingerprint

Cite this