Literature DB >> 23042217

A blood gene expression marker of early Alzheimer's disease.

Katie Lunnon1, Martina Sattlecker, Simon J Furney, Giovanni Coppola, Andrew Simmons, Petroula Proitsi, Michelle K Lupton, Anbarasu Lourdusamy, Caroline Johnston, Hilkka Soininen, Iwona Kłoszewska, Patrizia Mecocci, Magda Tsolaki, Bruno Vellas, Daniel Geschwind, Simon Lovestone, Richard Dobson, Angela Hodges.   

Abstract

A marker of Alzheimer's disease (AD) that can accurately diagnose disease at the earliest stage would significantly support efforts to develop treatments for early intervention. We have sought to determine the sensitivity and specificity of peripheral blood gene expression as a diagnostic marker of AD using data generated on HT-12v3 BeadChips. We first developed an AD diagnostic classifier in a training cohort of 78 AD and 78 control blood samples and then tested its performance in a validation group of 26 AD and 26 control and 118 mild cognitive impairment (MCI) subjects who were likely to have an AD-endpoint. A 48 gene classifier achieved an accuracy of 75% in the AD and control validation group. Comparisons were made with a classifier developed using structural MRI measures, where both measures were available in the same individuals. In AD and control subjects, the gene expression classifier achieved an accuracy of 70% compared to 85% using MRI. Bootstrapping validation produced expression and MRI classifiers with mean accuracies of 76% and 82%, respectively, demonstrating better concordance between these two classifiers than achieved in a single validation population. We conclude there is potential for blood expression to be a marker for AD. The classifier also predicts a large number of people with MCI, who are likely to develop AD, are more AD-like than normal with 76% of subjects classified as AD rather than control. Many of these people do not have overt brain atrophy, which is known to emerge around the time of AD diagnosis, suggesting the expression classifier may detect AD earlier in the prodromal phase. However, we accept these results could also represent a marker of diseases sharing common etiology.

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Year:  2013        PMID: 23042217     DOI: 10.3233/JAD-2012-121363

Source DB:  PubMed          Journal:  J Alzheimers Dis        ISSN: 1387-2877            Impact factor:   4.472


  39 in total

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Authors:  Anna Antonell; Albert Lladó; Raquel Sánchez-Valle; Coral Sanfeliu; Teresa Casserras; Lorena Rami; Cristina Muñoz-García; Adrià Dangla-Valls; Mircea Balasa; Patricia Boya; Susana G Kalko; José Luis Molinuevo
Journal:  Mol Neurobiol       Date:  2015-10-28       Impact factor: 5.590

2.  Blood methylomic signatures of presymptomatic dementia in elderly subjects with type 2 diabetes mellitus.

Authors:  Katie Lunnon; Rebecca G Smith; Itzik Cooper; Lior Greenbaum; Jonathan Mill; Michal Schnaider Beeri
Journal:  Neurobiol Aging       Date:  2014-12-24       Impact factor: 4.673

Review 3.  Analysis of the transcriptome in molecular epidemiology studies.

Authors:  Cliona M McHale; Luoping Zhang; Reuben Thomas; Martyn T Smith
Journal:  Environ Mol Mutagen       Date:  2013-08-01       Impact factor: 3.216

Review 4.  The future of blood-based biomarkers for Alzheimer's disease.

Authors:  Kim Henriksen; Sid E O'Bryant; Harald Hampel; John Q Trojanowski; Thomas J Montine; Andreas Jeromin; Kaj Blennow; Anders Lönneborg; Tony Wyss-Coray; Holly Soares; Chantal Bazenet; Magnus Sjögren; William Hu; Simon Lovestone; Morten A Karsdal; Michael W Weiner
Journal:  Alzheimers Dement       Date:  2013-07-11       Impact factor: 21.566

Review 5.  The mitochondrial epigenome: a role in Alzheimer's disease?

Authors:  Matthew Devall; Jonathan Mill; Katie Lunnon
Journal:  Epigenomics       Date:  2014       Impact factor: 4.778

6.  Common Aging Signature in the Peripheral Blood of Vascular Dementia and Alzheimer's Disease.

Authors:  Hongbo Luo; Guangchun Han; Jiajia Wang; Fan Zeng; Yuanming Li; Shaoju Shao; Fuhai Song; Zhouxian Bai; Xing Peng; Yan-Jiang Wang; Xiangqun Shi; Hongxing Lei
Journal:  Mol Neurobiol       Date:  2015-06-23       Impact factor: 5.590

7.  Cerebellar degeneration-related autoantigen 1 (CDR1) gene expression in Alzheimer's disease.

Authors:  Paolo Bosco; Rosario Spada; Salvatore Caniglia; Maria Grazia Salluzzo; Michele Salemi
Journal:  Neurol Sci       Date:  2014-04-29       Impact factor: 3.307

8.  Genome-wide transcriptome analysis identifies novel dysregulated genes implicated in Alzheimer's pathology.

Authors:  Kwangsik Nho; Kelly Nudelman; Mariet Allen; Angela Hodges; Sungeun Kim; Shannon L Risacher; Liana G Apostolova; Kuang Lin; Katie Lunnon; Xue Wang; Jeremy D Burgess; Nilüfer Ertekin-Taner; Ronald C Petersen; Lisu Wang; Zhenhao Qi; Aiqing He; Isaac Neuhaus; Vishal Patel; Tatiana Foroud; Kelley M Faber; Simon Lovestone; Andrew Simmons; Michael W Weiner; Andrew J Saykin
Journal:  Alzheimers Dement       Date:  2020-08-05       Impact factor: 21.566

9.  Transcriptomics of cortical gray matter thickness decline during normal aging.

Authors:  P Kochunov; J Charlesworth; A Winkler; L E Hong; T E Nichols; J E Curran; E Sprooten; N Jahanshad; P M Thompson; M P Johnson; J W Kent; B A Landman; B Mitchell; S A Cole; T D Dyer; E K Moses; H H H Goring; L Almasy; R Duggirala; R L Olvera; D C Glahn; J Blangero
Journal:  Neuroimage       Date:  2013-05-24       Impact factor: 6.556

Review 10.  Epigenetic studies in Alzheimer's disease: current findings, caveats, and considerations for future studies.

Authors:  Katie Lunnon; Jonathan Mill
Journal:  Am J Med Genet B Neuropsychiatr Genet       Date:  2013-09-13       Impact factor: 3.568

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