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Samantha Burnham | Research Statistician
17 June 2013
CSIRO MATHEMATICS INFORMATICS AND STATISTICS | PREVENTATIVE HEALTH
AIBL: A blood-based predictor for
neocortical Aβ burden
Hypothetical model of dynamic biomarkers of the Alzheimer’s pathological cascade, Clifford R Jack Jr, David S
Knopman, et al. Lancet Neurol 2010; 9: 119–28
The Hypothesis
Bioinformatics and Biostatistics | Sam Burnham2 |
Motivation
Bioinformatics and Biostatistics | Sam Burnham3 |
Amyloid β deposition, neurodegeneration, and cognitive decline in sporadic Alzheimer's disease: a prospective
cohort study, V.L. Villemagne, S.C. Burnham, et al. Lancet Neurol 2013; 12 (4): 357-67
Cohorts
Bioinformatics and Biostatistics | Sam Burnham4 |
Methods
Bioinformatics and Biostatistics | Sam Burnham5 |
NAB
Demographics
Blood
Measures
=
• SUVR
• + vs -
• Age
• Gender
• ...
• Blood 1
• Blood 2
• ...
• Blood 176
Cross Validate
Validate
• Base Model
• Full model
Check Value Added
Random Forest
Results
Model Markers AIBL Imaged Cohort
Sens%
(SD%)
Spec%
(SD%)
AUC%
(SD%)
M1
Age, APOE Genotype, CXCL-
13, IgM-1, IL-17, PPY, VCAM-
1, Aβ1-42, CDR sum of boxes
79.6
(1.3)
82.4
(1.2)
87.6
(0.7)
M2
Age, APOE Genotype, CXCL-
13, IgM-1, IL-17, PPY, VCAM-
1, Aβ1-42
79.6
(1.6)
79.4
(1.4)
83.9
(1.0)
M3
Age, CXCL-13, IgM-1, IL-17,
PPY, VCAM-1, Aβ1-42
73.2
(1.8)
73.3
(1.8)
80.8
(1.7)
M4
Age, APOE Genotype, CDR
sum of boxes
71.4
(1.1)
71.5
(1.1)
78.3
(0.8)
M5 Age, CDR sum of boxes
69.0
(2.1)
68.9
(2.2)
76.0
(2.0)
M6 Age, APOE Genotype
66.7
(1.6)
66.7
(1.6)
70.2
(1.3)
Bioinformatics and Biostatistics | Sam Burnham6 |
A blood-based predictor for neocortical Aβ
burden in Alzheimer’s disease: results from
the AIBL study, S.C. Burnham, N.G. Faux, et
al. Mol Psy 2013; doi:10.1038/mp.2013.40
Validation
Model Markers ADNI Imaged
Cohort
Sens
%
Spec
%
AUC
%
M1
Age, APOE Genotype, CXCL-13,
IgM-1, IL-17, PPY, VCAM-1, Aβ1-
42, CDR sum of boxes
78.3 76.3 84.7
M2
Age, APOE Genotype, CXCL-13,
IgM-1, IL-17, PPY, VCAM-1, Aβ1-42
73.9 74.6 81.7
M3
Age, CXCL-13, IgM-1, IL-17, PPY,
VCAM-1, Aβ1-42
68.1 73.6 68.8
M4
Age, APOE Genotype, CDR sum
of boxes
72.7 67.9 73.7
M5 Age, CDR sum of boxes 59.1 62.3 64.5
M6 Age, APOE Genotype 77.3 62.3 67.8
Bioinformatics and Biostatistics | Sam Burnham7 |
A blood-based predictor for neocortical Aβ
burden in Alzheimer’s disease: results from
the AIBL study, S.C. Burnham, N.G. Faux, et
al. Mol Psy 2013; doi:10.1038/mp.2013.40
Other Support
Bioinformatics and Biostatistics | Sam Burnham8 |
A blood-based predictor for
neocortical Aβ burden in
Alzheimer’s disease: results
from the AIBL study, S.C.
Burnham, N.G. Faux, et al. Mol
Psy 2013;
doi:10.1038/mp.2013.40
Summary
• Early detection is critical
• Likely need multimodal and multistage screening process
• Require cheap and non-invasive medium for widespread screen
• Proof of principal for blood biomarker use
• Composite scores, unlikely to be a single marker
• Validation is imperative
Bioinformatics and Biostatistics | Sam Burnham9 |
Acknowledgments
Bioinformatics and Biostatistics | Sam Burnham10 |
AIBL is a large collaborative study and a complete list
of contributors can be found at www.aibl.csiro.au
AIBL is funded in part by a grant from the Science and
Industry Endowment Fund. We thank all who took part
in the study.
Acknowledgements and
thanks to the AIBL study
participants and their
families
David Ames
Arti Appannah
Mary Barnes
Kevin Barnham
Justin Bedo
Shayne Bellingham
Lynette Bon
Pierrick Bourgeat
Belinda Brown
Rachel Buckley
Samantha Burnham
Ashley Bush
Graeme Chandler
Prastishtha Chatterjee
Karren Chen
Roger Clarnette
Steven Collins
Ian Cooke
Tiffany Cowie
Kay Cox
Rhona Creegan
Emily Cuningham
David Darby
Karl Deruyck
Patricia Desmond
Hang Ding
James Doecke
Vincent Dore
Harriet Downing
Belinda Dridan
Konsta Duesing
Denise El- Sheikh
Kathryn Ellis
Michael Fahey
Maree Farrow
Noel Faux
Michael Fenech
Jonathan Foster
Christopher Fowler
Maxime Francois
Jurgen Fripp
Shaun Frost
Sam Gardener
Simon Gibson
David Goth
Petra Graham
Veer Gupta
Garry Hannan
David Hansen
Karra Harrington
Richard Head
Andy Hill
Maryam Hor
Malcolm Horne
Brenda Huckstepp
Pete Hudson
Andrew Jones
Gareth Jones
Adrian Kamer
Yogi Kanagasingam
Mohan Karunanithi
Lisa Keam
Neil Killeen
Adam Kowalczyk
Debra Krause
Betty Krivdic
Rebecca Lachovitski
Chiou Peng Lam
Fiona Lamb
Nicola Lautenschlager
Simon Laws
Wayne Leifert
Nat Lenzo
Hugo Leroux
Falak Lftikhar
Qiao-Xin Li
Florence Lim
Yen Ying Lim
Teresa Lintern
Linda Lockett
Kathleen Lucas
James Lui
Lance Macaulay
Mark Mano
Georgia Martins
Ralph Martins
Paul Maruff
Colin Masters
Yumiko Matsumoto
Sabine Matthaes
Simon McBride
Rachel McKay
Andrew Milner
Alinda Mondal
Claire Montague
Lynette Moore
Audrey Muir
Rachel Mulligan
Tabitha Nash
Julie Nigro
Stewart Nuttall
Nathan O’Callaghan
Christopher O’Halloran
Graeme O'Keefe
Tim O’Meara
Kevin Ong
Lisa Osborne
Chaoyi Pang
Bernadette Parker
Glen Patten
Jeremiah Peiffer
Svetlana Pejoska
Lisa Penny
Keyla Perez
Kelly Pertile
Pramit Phal
Kerryn Pike
Stephanie Rainey-Smith
Parnesh Raniga
Alan Rembach
Carolina Restrepo
Malcolm Riley
Blaine Roberts
Jo Robertson
Mark Rodrigues
Alicia Rooney
Christopher Rowe
Rebecca Rumble
Tim Ryan
Olivier Salvado
Ian Saunders
Greg Savage
Brendan Silbert
Hamid Sohrabi
Julie Syrette
Cassandra Szoeke
Kevin Taddei
Tania Taddei
Michelle Tegg
Philip Thomas
Darshan Trivedi
Brett Trounson
Alison Tuckfield
Jose Varghese
Robyn Veljanovski
Giuseppe Verdile
Victor Villemagne
Irene Volitakis
Michael Vovos
Stacey Walker
Andrew Watt
Mike Weinborn
Andrea Wilson
Bill Wilson
Michael Woodward
Olga Yastrubetskaya
Paul Yates
Ping Zhang
Qing Zhang
Luping Zhou

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Scb alzforum

  • 1. Samantha Burnham | Research Statistician 17 June 2013 CSIRO MATHEMATICS INFORMATICS AND STATISTICS | PREVENTATIVE HEALTH AIBL: A blood-based predictor for neocortical Aβ burden
  • 2. Hypothetical model of dynamic biomarkers of the Alzheimer’s pathological cascade, Clifford R Jack Jr, David S Knopman, et al. Lancet Neurol 2010; 9: 119–28 The Hypothesis Bioinformatics and Biostatistics | Sam Burnham2 |
  • 3. Motivation Bioinformatics and Biostatistics | Sam Burnham3 | Amyloid β deposition, neurodegeneration, and cognitive decline in sporadic Alzheimer's disease: a prospective cohort study, V.L. Villemagne, S.C. Burnham, et al. Lancet Neurol 2013; 12 (4): 357-67
  • 5. Methods Bioinformatics and Biostatistics | Sam Burnham5 | NAB Demographics Blood Measures = • SUVR • + vs - • Age • Gender • ... • Blood 1 • Blood 2 • ... • Blood 176 Cross Validate Validate • Base Model • Full model Check Value Added Random Forest
  • 6. Results Model Markers AIBL Imaged Cohort Sens% (SD%) Spec% (SD%) AUC% (SD%) M1 Age, APOE Genotype, CXCL- 13, IgM-1, IL-17, PPY, VCAM- 1, Aβ1-42, CDR sum of boxes 79.6 (1.3) 82.4 (1.2) 87.6 (0.7) M2 Age, APOE Genotype, CXCL- 13, IgM-1, IL-17, PPY, VCAM- 1, Aβ1-42 79.6 (1.6) 79.4 (1.4) 83.9 (1.0) M3 Age, CXCL-13, IgM-1, IL-17, PPY, VCAM-1, Aβ1-42 73.2 (1.8) 73.3 (1.8) 80.8 (1.7) M4 Age, APOE Genotype, CDR sum of boxes 71.4 (1.1) 71.5 (1.1) 78.3 (0.8) M5 Age, CDR sum of boxes 69.0 (2.1) 68.9 (2.2) 76.0 (2.0) M6 Age, APOE Genotype 66.7 (1.6) 66.7 (1.6) 70.2 (1.3) Bioinformatics and Biostatistics | Sam Burnham6 | A blood-based predictor for neocortical Aβ burden in Alzheimer’s disease: results from the AIBL study, S.C. Burnham, N.G. Faux, et al. Mol Psy 2013; doi:10.1038/mp.2013.40
  • 7. Validation Model Markers ADNI Imaged Cohort Sens % Spec % AUC % M1 Age, APOE Genotype, CXCL-13, IgM-1, IL-17, PPY, VCAM-1, Aβ1- 42, CDR sum of boxes 78.3 76.3 84.7 M2 Age, APOE Genotype, CXCL-13, IgM-1, IL-17, PPY, VCAM-1, Aβ1-42 73.9 74.6 81.7 M3 Age, CXCL-13, IgM-1, IL-17, PPY, VCAM-1, Aβ1-42 68.1 73.6 68.8 M4 Age, APOE Genotype, CDR sum of boxes 72.7 67.9 73.7 M5 Age, CDR sum of boxes 59.1 62.3 64.5 M6 Age, APOE Genotype 77.3 62.3 67.8 Bioinformatics and Biostatistics | Sam Burnham7 | A blood-based predictor for neocortical Aβ burden in Alzheimer’s disease: results from the AIBL study, S.C. Burnham, N.G. Faux, et al. Mol Psy 2013; doi:10.1038/mp.2013.40
  • 8. Other Support Bioinformatics and Biostatistics | Sam Burnham8 | A blood-based predictor for neocortical Aβ burden in Alzheimer’s disease: results from the AIBL study, S.C. Burnham, N.G. Faux, et al. Mol Psy 2013; doi:10.1038/mp.2013.40
  • 9. Summary • Early detection is critical • Likely need multimodal and multistage screening process • Require cheap and non-invasive medium for widespread screen • Proof of principal for blood biomarker use • Composite scores, unlikely to be a single marker • Validation is imperative Bioinformatics and Biostatistics | Sam Burnham9 |
  • 10. Acknowledgments Bioinformatics and Biostatistics | Sam Burnham10 | AIBL is a large collaborative study and a complete list of contributors can be found at www.aibl.csiro.au AIBL is funded in part by a grant from the Science and Industry Endowment Fund. We thank all who took part in the study. Acknowledgements and thanks to the AIBL study participants and their families David Ames Arti Appannah Mary Barnes Kevin Barnham Justin Bedo Shayne Bellingham Lynette Bon Pierrick Bourgeat Belinda Brown Rachel Buckley Samantha Burnham Ashley Bush Graeme Chandler Prastishtha Chatterjee Karren Chen Roger Clarnette Steven Collins Ian Cooke Tiffany Cowie Kay Cox Rhona Creegan Emily Cuningham David Darby Karl Deruyck Patricia Desmond Hang Ding James Doecke Vincent Dore Harriet Downing Belinda Dridan Konsta Duesing Denise El- Sheikh Kathryn Ellis Michael Fahey Maree Farrow Noel Faux Michael Fenech Jonathan Foster Christopher Fowler Maxime Francois Jurgen Fripp Shaun Frost Sam Gardener Simon Gibson David Goth Petra Graham Veer Gupta Garry Hannan David Hansen Karra Harrington Richard Head Andy Hill Maryam Hor Malcolm Horne Brenda Huckstepp Pete Hudson Andrew Jones Gareth Jones Adrian Kamer Yogi Kanagasingam Mohan Karunanithi Lisa Keam Neil Killeen Adam Kowalczyk Debra Krause Betty Krivdic Rebecca Lachovitski Chiou Peng Lam Fiona Lamb Nicola Lautenschlager Simon Laws Wayne Leifert Nat Lenzo Hugo Leroux Falak Lftikhar Qiao-Xin Li Florence Lim Yen Ying Lim Teresa Lintern Linda Lockett Kathleen Lucas James Lui Lance Macaulay Mark Mano Georgia Martins Ralph Martins Paul Maruff Colin Masters Yumiko Matsumoto Sabine Matthaes Simon McBride Rachel McKay Andrew Milner Alinda Mondal Claire Montague Lynette Moore Audrey Muir Rachel Mulligan Tabitha Nash Julie Nigro Stewart Nuttall Nathan O’Callaghan Christopher O’Halloran Graeme O'Keefe Tim O’Meara Kevin Ong Lisa Osborne Chaoyi Pang Bernadette Parker Glen Patten Jeremiah Peiffer Svetlana Pejoska Lisa Penny Keyla Perez Kelly Pertile Pramit Phal Kerryn Pike Stephanie Rainey-Smith Parnesh Raniga Alan Rembach Carolina Restrepo Malcolm Riley Blaine Roberts Jo Robertson Mark Rodrigues Alicia Rooney Christopher Rowe Rebecca Rumble Tim Ryan Olivier Salvado Ian Saunders Greg Savage Brendan Silbert Hamid Sohrabi Julie Syrette Cassandra Szoeke Kevin Taddei Tania Taddei Michelle Tegg Philip Thomas Darshan Trivedi Brett Trounson Alison Tuckfield Jose Varghese Robyn Veljanovski Giuseppe Verdile Victor Villemagne Irene Volitakis Michael Vovos Stacey Walker Andrew Watt Mike Weinborn Andrea Wilson Bill Wilson Michael Woodward Olga Yastrubetskaya Paul Yates Ping Zhang Qing Zhang Luping Zhou