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6 results on '"Bernadette McGuinness"'

1. Untargeted metabolomic analysis of human plasma indicates differentially affected polyamine and L-arginine metabolism in mild cognitive impairment subjects converting to Alzheimer's disease.

Author

Stewart F Graham, Olivier P Chevallier, Christopher T Elliott, Christian Hölscher, Janet Johnston, Bernadette McGuinness, Patrick G Kehoe, Anthony Peter Passmore, and Brian D Green

Subjects
Medicine, Science
Abstract

This study combined high resolution mass spectrometry (HRMS), advanced chemometrics and pathway enrichment analysis to analyse the blood metabolome of patients attending the memory clinic: cases of mild cognitive impairment (MCI; n = 16), cases of MCI who upon subsequent follow-up developed Alzheimer's disease (MCI_AD; n = 19), and healthy age-matched controls (Ctrl; n = 37). Plasma was extracted in acetonitrile and applied to an Acquity UPLC HILIC (1.7μm x 2.1 x 100 mm) column coupled to a Xevo G2 QTof mass spectrometer using a previously optimised method. Data comprising 6751 spectral features were used to build an OPLS-DA statistical model capable of accurately distinguishing Ctrl, MCI and MCI_AD. The model accurately distinguished (R2 = 99.1%; Q2 = 97%) those MCI patients who later went on to develop AD. S-plots were used to shortlist ions of interest which were responsible for explaining the maximum amount of variation between patient groups. Metabolite database searching and pathway enrichment analysis indicated disturbances in 22 biochemical pathways, and excitingly it discovered two interlinked areas of metabolism (polyamine metabolism and L-Arginine metabolism) were differentially disrupted in this well-defined clinical cohort. The optimised untargeted HRMS methods described herein not only demonstrate that it is possible to distinguish these pathologies in human blood but also that MCI patients 'at risk' from AD could be predicted up to 2 years earlier than conventional clinical diagnosis. Blood-based metabolite profiling of plasma from memory clinic patients is a novel and feasible approach in improving MCI and AD diagnosis and, refining clinical trials through better patient stratification.

Published
2015
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2. Gene-wide analysis detects two new susceptibility genes for Alzheimer's disease.

Author

Valentina Escott-Price, Céline Bellenguez, Li-San Wang, Seung-Hoan Choi, Denise Harold, Lesley Jones, Peter Holmans, Amy Gerrish, Alexey Vedernikov, Alexander Richards, Anita L DeStefano, Jean-Charles Lambert, Carla A Ibrahim-Verbaas, Adam C Naj, Rebecca Sims, Gyungah Jun, Joshua C Bis, Gary W Beecham, Benjamin Grenier-Boley, Giancarlo Russo, Tricia A Thornton-Wells, Nicola Denning, Albert V Smith, Vincent Chouraki, Charlene Thomas, M Arfan Ikram, Diana Zelenika, Badri N Vardarajan, Yoichiro Kamatani, Chiao-Feng Lin, Helena Schmidt, Brian Kunkle, Melanie L Dunstan, Maria Vronskaya, United Kingdom Brain Expression Consortium, Andrew D Johnson, Agustin Ruiz, Marie-Thérèse Bihoreau, Christiane Reitz, Florence Pasquier, Paul Hollingworth, Olivier Hanon, Annette L Fitzpatrick, Joseph D Buxbaum, Dominique Campion, Paul K Crane, Clinton Baldwin, Tim Becker, Vilmundur Gudnason, Carlos Cruchaga, David Craig, Najaf Amin, Claudine Berr, Oscar L Lopez, Philip L De Jager, Vincent Deramecourt, Janet A Johnston, Denis Evans, Simon Lovestone, Luc Letenneur, Isabel Hernández, David C Rubinsztein, Gudny Eiriksdottir, Kristel Sleegers, Alison M Goate, Nathalie Fiévet, Matthew J Huentelman, Michael Gill, Kristelle Brown, M Ilyas Kamboh, Lina Keller, Pascale Barberger-Gateau, Bernadette McGuinness, Eric B Larson, Amanda J Myers, Carole Dufouil, Stephen Todd, David Wallon, Seth Love, Ekaterina Rogaeva, John Gallacher, Peter St George-Hyslop, Jordi Clarimon, Alberto Lleo, Anthony Bayer, Debby W Tsuang, Lei Yu, Magda Tsolaki, Paola Bossù, Gianfranco Spalletta, Petra Proitsi, John Collinge, Sandro Sorbi, Florentino Sanchez Garcia, Nick C Fox, John Hardy, Maria Candida Deniz Naranjo, Paolo Bosco, Robert Clarke, Carol Brayne, Daniela Galimberti, Elio Scarpini, Ubaldo Bonuccelli, Michelangelo Mancuso, Gabriele Siciliano, Susanne Moebus, Patrizia Mecocci, Maria Del Zompo, Wolfgang Maier, Harald Hampel, Alberto Pilotto, Ana Frank-García, Francesco Panza, Vincenzo Solfrizzi, Paolo Caffarra, Benedetta Nacmias, William Perry, Manuel Mayhaus, Lars Lannfelt, Hakon Hakonarson, Sabrina Pichler, Minerva M Carrasquillo, Martin Ingelsson, Duane Beekly, Victoria Alvarez, Fanggeng Zou, Otto Valladares, Steven G Younkin, Eliecer Coto, Kara L Hamilton-Nelson, Wei Gu, Cristina Razquin, Pau Pastor, Ignacio Mateo, Michael J Owen, Kelley M Faber, Palmi V Jonsson, Onofre Combarros, Michael C O'Donovan, Laura B Cantwell, Hilkka Soininen, Deborah Blacker, Simon Mead, Thomas H Mosley, David A Bennett, Tamara B Harris, Laura Fratiglioni, Clive Holmes, Renee F A G de Bruijn, Peter Passmore, Thomas J Montine, Karolien Bettens, Jerome I Rotter, Alexis Brice, Kevin Morgan, Tatiana M Foroud, Walter A Kukull, Didier Hannequin, John F Powell, Michael A Nalls, Karen Ritchie, Kathryn L Lunetta, John S K Kauwe, Eric Boerwinkle, Matthias Riemenschneider, Mercè Boada, Mikko Hiltunen, Eden R Martin, Reinhold Schmidt, Dan Rujescu, Jean-François Dartigues, Richard Mayeux, Christophe Tzourio, Albert Hofman, Markus M Nöthen, Caroline Graff, Bruce M Psaty, Jonathan L Haines, Mark Lathrop, Margaret A Pericak-Vance, Lenore J Launer, Christine Van Broeckhoven, Lindsay A Farrer, Cornelia M van Duijn, Alfredo Ramirez, Sudha Seshadri, Gerard D Schellenberg, Philippe Amouyel, Julie Williams, and Cardiovascular Health Study (CHS)

Subjects
Medicine, Science
Abstract

BACKGROUND:Alzheimer's disease is a common debilitating dementia with known heritability, for which 20 late onset susceptibility loci have been identified, but more remain to be discovered. This study sought to identify new susceptibility genes, using an alternative gene-wide analytical approach which tests for patterns of association within genes, in the powerful genome-wide association dataset of the International Genomics of Alzheimer's Project Consortium, comprising over 7 m genotypes from 25,580 Alzheimer's cases and 48,466 controls. PRINCIPAL FINDINGS:In addition to earlier reported genes, we detected genome-wide significant loci on chromosomes 8 (TP53INP1, p = 1.4×10-6) and 14 (IGHV1-67 p = 7.9×10-8) which indexed novel susceptibility loci. SIGNIFICANCE:The additional genes identified in this study, have an array of functions previously implicated in Alzheimer's disease, including aspects of energy metabolism, protein degradation and the immune system and add further weight to these pathways as potential therapeutic targets in Alzheimer's disease.

Published
2014
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3. Correction: Genetic Evidence Implicates the Immune System and Cholesterol Metabolism in the Aetiology of Alzheimer's Disease.

Author

Lesley Jones, Peter A. Holmans, Marian L. Hamshere, Denise Harold, Valentina Moskvina, Dobril Ivanov, Andrew Pocklington, Richard Abraham, Paul Hollingworth, Rebecca Sims, Amy Gerrish, Jaspreet Singh Pahwa, Nicola Jones, Alexandra Stretton, Angharad R. Morgan, Simon Lovestone, John Powell, Petroula Proitsi, Michelle K. Lupton, Carol Brayne, David C. Rubinsztein, Michael Gill, Brian Lawlor, Aoibhinn Lynch, Kevin Morgan, Kristelle S. Brown, Peter A. Passmore, David Craig, Bernadette McGuinness, Stephen Todd, Clive Holmes, David Mann, A. David Smith, Seth Love, Patrick G. Kehoe, Simon Mead, Nick Fox, Martin Rossor, John Collinge, Wolfgang Maier, Frank Jessen, Britta Schürmann, Hendrik van den Bussche, Isabella Heuser, Oliver Peters, Johannes Kornhuber, Jens Wiltfang, Martin Dichgans, Lutz Frölich, Harald Hampel, Michael Hüll, Dan Rujescu, Alison M. Goate, John S. K. Kauwe, Carlos Cruchaga, Petra Nowotny, John C. Morris, Kevin Mayo, Gill Livingston, Nicholas J. Bass, Hugh Gurling, Andrew McQuillin, Rhian Gwilliam, Panos Deloukas, Ammar Al-Chalabi, Christopher E. Shaw, Andrew B. Singleton, Rita Guerreiro, Thomas W. Mühleisen, Markus M. Nöthen, Susanne Moebus, Karl-Heinz Jöckel, Norman Klopp, H.-Erich Wichmann, Eckhard Rüther, Minerva M. Carrasquillo, V. Shane Pankratz, Steven G. Younkin, John Hardy, Michael C. O'Donovan, Michael J. Owen, and Julie Williams

Subjects
Medicine, Science
Published
2011
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4. Genetic evidence implicates the immune system and cholesterol metabolism in the aetiology of Alzheimer's disease.

Author

Lesley Jones, Peter A Holmans, Marian L Hamshere, Denise Harold, Valentina Moskvina, Dobril Ivanov, Andrew Pocklington, Richard Abraham, Paul Hollingworth, Rebecca Sims, Amy Gerrish, Jaspreet Singh Pahwa, Nicola Jones, Alexandra Stretton, Angharad R Morgan, Simon Lovestone, John Powell, Petroula Proitsi, Michelle K Lupton, Carol Brayne, David C Rubinsztein, Michael Gill, Brian Lawlor, Aoibhinn Lynch, Kevin Morgan, Kristelle S Brown, Peter A Passmore, David Craig, Bernadette McGuinness, Stephen Todd, Clive Holmes, David Mann, A David Smith, Seth Love, Patrick G Kehoe, Simon Mead, Nick Fox, Martin Rossor, John Collinge, Wolfgang Maier, Frank Jessen, Britta Schürmann, Reinhard Heun, Heike Kölsch, Hendrik van den Bussche, Isabella Heuser, Oliver Peters, Johannes Kornhuber, Jens Wiltfang, Martin Dichgans, Lutz Frölich, Harald Hampel, Michael Hüll, Dan Rujescu, Alison M Goate, John S K Kauwe, Carlos Cruchaga, Petra Nowotny, John C Morris, Kevin Mayo, Gill Livingston, Nicholas J Bass, Hugh Gurling, Andrew McQuillin, Rhian Gwilliam, Panos Deloukas, Ammar Al-Chalabi, Christopher E Shaw, Andrew B Singleton, Rita Guerreiro, Thomas W Mühleisen, Markus M Nöthen, Susanne Moebus, Karl-Heinz Jöckel, Norman Klopp, H-Erich Wichmann, Eckhard Rüther, Minerva M Carrasquillo, V Shane Pankratz, Steven G Younkin, John Hardy, Michael C O'Donovan, Michael J Owen, and Julie Williams

Subjects
Medicine, Science
Abstract

BackgroundLate Onset Alzheimer's disease (LOAD) is the leading cause of dementia. Recent large genome-wide association studies (GWAS) identified the first strongly supported LOAD susceptibility genes since the discovery of the involvement of APOE in the early 1990s. We have now exploited these GWAS datasets to uncover key LOAD pathophysiological processes.MethodologyWe applied a recently developed tool for mining GWAS data for biologically meaningful information to a LOAD GWAS dataset. The principal findings were then tested in an independent GWAS dataset.Principal findingsWe found a significant overrepresentation of association signals in pathways related to cholesterol metabolism and the immune response in both of the two largest genome-wide association studies for LOAD.SignificanceProcesses related to cholesterol metabolism and the innate immune response have previously been implicated by pathological and epidemiological studies of Alzheimer's disease, but it has been unclear whether those findings reflected primary aetiological events or consequences of the disease process. Our independent evidence from two large studies now demonstrates that these processes are aetiologically relevant, and suggests that they may be suitable targets for novel and existing therapeutic approaches.

Published
2010
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5. Concordant association of insulin degrading enzyme gene (IDE) variants with IDE mRNA, Abeta, and Alzheimer's disease.

Author

Minerva M Carrasquillo, Olivia Belbin, Fanggeng Zou, Mariet Allen, Nilufer Ertekin-Taner, Morad Ansari, Samantha L Wilcox, Mariah R Kashino, Li Ma, Linda H Younkin, Samuel G Younkin, Curtis S Younkin, Toros A Dincman, Melissa E Howard, Chanley C Howell, Chloe M Stanton, Christopher M Watson, Michael Crump, Veronique Vitart, Caroline Hayward, Nicholas D Hastie, Igor Rudan, Harry Campbell, Ozren Polasek, Kristelle Brown, Peter Passmore, David Craig, Bernadette McGuinness, Stephen Todd, Patrick G Kehoe, David M Mann, A David Smith, Helen Beaumont, Donald Warden, Clive Holmes, Reinhard Heun, Heike Kölsch, Noor Kalsheker, V Shane Pankratz, Dennis W Dickson, Neill R Graff-Radford, Ronald C Petersen, Alan F Wright, Steven G Younkin, and Kevin Morgan

Subjects
Medicine, Science
Abstract

BACKGROUND:The insulin-degrading enzyme gene (IDE) is a strong functional and positional candidate for late onset Alzheimer's disease (LOAD). METHODOLOGY/PRINCIPAL FINDINGS:We examined conserved regions of IDE and its 10 kb flanks in 269 AD cases and 252 controls thereby identifying 17 putative functional polymorphisms. These variants formed eleven haplotypes that were tagged with ten variants. Four of these showed significant association with IDE transcript levels in samples from 194 LOAD cerebella. The strongest, rs6583817, which has not previously been reported, showed unequivocal association (p = 1.5x10(-8), fold-increase = 2.12,); the eleven haplotypes were also significantly associated with transcript levels (global p = 0.003). Using an in vitro dual luciferase reporter assay, we found that rs6583817 increases reporter gene expression in Be(2)-C (p = 0.006) and HepG2 (p = 0.02) cell lines. Furthermore, using data from a recent genome-wide association study of two Croatian isolated populations (n = 1,879), we identified a proxy for rs6583817 that associated significantly with decreased plasma Abeta40 levels (ss = -0.124, p = 0.011) and total measured plasma Abeta levels (b = -0.130, p = 0.009). Finally, rs6583817 was associated with decreased risk of LOAD in 3,891 AD cases and 3,605 controls. (OR = 0.87, p = 0.03), and the eleven IDE haplotypes (global p = 0.02) also showed significant association. CONCLUSIONS:Thus, a previously unreported variant unequivocally associated with increased IDE expression was also associated with reduced plasma Abeta40 and decreased LOAD susceptibility. Genetic association between LOAD and IDE has been difficult to replicate. Our findings suggest that targeted testing of expression SNPs (eSNPs) strongly associated with altered transcript levels in autopsy brain samples may be a powerful way to identify genetic associations with LOAD that would otherwise be difficult to detect.

Published
2010
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6. Untargeted metabolomic analysis of human plasma indicates differentially affected polyamine and L-arginine metabolism in mild cognitive impairment subjects converting to Alzheimer's disease

Author

Stewart F, Graham, Olivier P, Chevallier, Christopher T, Elliott, Christian, Hölscher, Janet, Johnston, Bernadette, McGuinness, Patrick G, Kehoe, Anthony Peter, Passmore, and Brian D, Green

Subjects
Male, Arginine, Mass Spectrometry, Alzheimer Disease, Predictive Value of Tests, Case-Control Studies, Polyamines, Humans, Metabolomics, Cognitive Dysfunction, Female, Biomarkers, Aged, Research Article
Abstract

This study combined high resolution mass spectrometry (HRMS), advanced chemometrics and pathway enrichment analysis to analyse the blood metabolome of patients attending the memory clinic: cases of mild cognitive impairment (MCI; n = 16), cases of MCI who upon subsequent follow-up developed Alzheimer’s disease (MCI_AD; n = 19), and healthy age-matched controls (Ctrl; n = 37). Plasma was extracted in acetonitrile and applied to an Acquity UPLC HILIC (1.7μm x 2.1 x 100 mm) column coupled to a Xevo G2 QTof mass spectrometer using a previously optimised method. Data comprising 6751 spectral features were used to build an OPLS-DA statistical model capable of accurately distinguishing Ctrl, MCI and MCI_AD. The model accurately distinguished (R2 = 99.1%; Q2 = 97%) those MCI patients who later went on to develop AD. S-plots were used to shortlist ions of interest which were responsible for explaining the maximum amount of variation between patient groups. Metabolite database searching and pathway enrichment analysis indicated disturbances in 22 biochemical pathways, and excitingly it discovered two interlinked areas of metabolism (polyamine metabolism and L-Arginine metabolism) were differentially disrupted in this well-defined clinical cohort. The optimised untargeted HRMS methods described herein not only demonstrate that it is possible to distinguish these pathologies in human blood but also that MCI patients ‘at risk’ from AD could be predicted up to 2 years earlier than conventional clinical diagnosis. Blood-based metabolite profiling of plasma from memory clinic patients is a novel and feasible approach in improving MCI and AD diagnosis and, refining clinical trials through better patient stratification.

Published
2014

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