- Email: [email protected]
MULTILEVEL ANALYSIS OF BIOMARKER POOL FOR ALZHEIMER’S DISEASE RISK IN A NORTH INDIAN POPULATION
P878
Poster Presentations: Tuesday, July 26, 2016
2.94). Conclusions: Elevated plasma tau is associated with neuroimaging measures of neurodegeneration and with worse memory performance in a population based cohort. Additional studies are needed to verify these findings and further elucidate the connection between plasma tau levels, neurodegeneration, and cognition. P3-153
MULTILEVEL ANALYSIS OF BIOMARKER POOL FOR ALZHEIMER’S DISEASE RISK IN A NORTH INDIAN POPULATION 1
1
2
Ritushree Kukreti , Puneet Talwar , Suman Kushwaha , Rachna Agarwal2, 1CSIR-Institute of Genomics and Integrative Biology, Delhi, India; 2Institute of Human Behaviour and Allied Sciences, Delhi, India. Contact e-mail: [email protected] Background: Alzheimer’s disease (AD) is a progressive neurode-
generative disease with complex pathophysiology and multifactorial etiology. Here, we aim to examine the gene-environment interaction with reference to genetic variants from AD associated genes, blood biomarkers, clinical variables and demographic factors as predictors of AD risk. Methods: We performed identification of biomarker pool in case-control study involving 108 AD cases and 159 non-demented healthy controls to examine association among multiple biomarkers. Results: APOE genotyping revealed that e4 allele frequency was significantly high (p value¼0.0001, OR¼2.66, 95%CI¼1.58-4.46) in AD as compared to controls whereas APOE e2 (p: 0.043, OR¼0.29, CI¼0.07-1.10) was overrepresented in controls. In biochemical assays, a significant difference (p<0.05) in levels of copper, free copper, zinc, iron, epidermal growth factor receptor (EGFR), copper/zinc and leptin was observed between AD patients and controls. Then, we created the AD risk-score(ADRS) as linear combination of seven candidate markers involving age, APOE e4 allele and levels of iron, leptin, EGFR, albumin and Cu/Zn ratio. The area under the ROC curve of the combined ADRS panel for predicting AD risk was higher (AUC¼0.83, p<0.0001, 95%CI¼0.77-0.89), as compared to individual parameters alone. The sensitivity and specificity was found to be 67.8% and 83.7% respectively. Conclusions: The findings provide evidence on the multifactorial etiology of AD and demonstrated ability of a panel involving seven biomarkers to discriminate AD cases from non-demented healthy controls. P3-154
PLASMA BIOMARKERS OF NEOCORTICAL AMYLOID BURDEN: AN IN-DEPTH PLASMA PROFILE USING LC-MS
Nicholas J. Ashton1,2, Alejo Narvardo3, Steven Lynham2, Malcolm Ward2, Veer Gupta4,5, Pratishtha Chatterjee6,7, Kathryn Goozee4,6,8,9,10, McCusker KARVIAH Research Group11, Eugene Hone4,5, Steve Pedrini4,5, Stephanie R. Rainey-Smith4,12, Simon M. Laws4,5, Ashley I. Bush5,13,14, Christopher C. Rowe14,15, David Ames14,16,17, Victor L. Villemagne14,18, Colin L. Masters13,14, AIBL Research Group14, Simon Lovestone3, Ralph N. Martins4,5,9,12,14, Abdul Hye1,2, 1NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, United Kingdom; 2 Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom; 3University of Oxford, Oxford, United Kingdom; 4Edith Cowan University, Perth, Australia; 5Cooperative Research Centre for Mental Health, Melbourne, Australia; 6KaRa Institute of Neurological Diseases, Sydney, Australia; 7Macquarie University, Sydney, Australia; 8Faculty of Medicine and Health Sciences, Macquarie University, Sydney, Australia; 9School of Psychiatry and Clinical Neurosciences, University of Western Australia, Perth, Australia; 10The
Anglican Retirement Villages, Sydney, Australia; 11McCusker KARVIAH Research Group, Perth, Australia; 12Sir James McCusker Alzheimer’s Disease Research Unit (Hollywood Private Hospital), Perth, Australia; 13 The Florey Institute of Neuroscience and Mental Health, Melbourne, Australia; 14AIBL Research Group, Perth and Melbourne, Australia; 15 Austin Health, Melbourne, Australia; 16The University of Melbourne, Melbourne, Australia; 17National Ageing Research Institute, Melbourne, Australia; 18Department of Molecular Imaging and Therapy, Centre for PET, Austin Health, Heidelberg, Australia. Contact e-mail: nicholas.1. [email protected] Background: Neocortical amyloid burden (NAB) is an important risk factor for Alzheimer’s disease (AD) that precedes the onset of clinical symptoms. It has become critical to identify individuals at early stages of NAB deposition to recruit into clinical trials of disease-modifying therapeutics. Blood-based biomarkers predicting NAB would have great utility for enrichment of AD clinical trials, including large-scale prevention trials. Despite this, only a handful of studies have investigated plasma biomarkers of NAB (Thambisetty et al; Burnham et al; Kiddle et al), with one study utilising Mass Spectrometry (MS) (Ashton et al). MS has several advantages as a discovery tool over panel-based assays however its limited sensitivity and protein coverage have been a restricting factor. Here, we present an in-depth MS-based screen of cognitively normal (CN) participants with varying degree of NAB. The objective was to identify a peripheral signature of AD pathology which precedes clinical manifestation. Methods: A proteomic workflow combining immunodepletion, isobaric peptide labelling and Isoelectric focusing (IEF) was established as a sensitive and robust strategy for in-depth plasma exploration compared with other proteomic methodologies (unpublished). Protein identification and relative quantitation was performed by MS (Orbitrap Velos). This methodology was applied to n¼297 CN participants from the AIBL and KARVIAH cohorts. All participants underwent PET amyloid imaging at time of sampling with n¼187 having subsequent imaging at multiple time-points. Linear Models, Discriminant Analysis and Support Vector Machines were performed to establish a cross-sectional and longitudinal proteomic model of elevated NAB. Results: A refined proteomic strategy has demonstrated a reproducible workflow that can profile >1000 plasma proteins, accurately detecting low picogram levels (unpublished). In addition to increased dynamic range, proteins indicative of the central nervous system (CNS) such as myelin basic protein and neurogranin are routinely observed. This discovery methodology has allowed the generation of a novel prediction model for both baseline and prospective NAB. Conclusions: An in-depth MS-based workflow has confirmed CNS proteins are readily measureable in the periphery, which has enabled the most detailed proteomic screen of AD pathology to date. Further replication of these putative markers will be needed although this additional evidence illustrates the potential use of a blood-based strategy in AD.
P3-155
THYROID HORMONES AND ALZHEIMER’S DISEASE
Gustavo A. A. Santos1, Paulo Celso Pardi2, Niraldo Paulino1, Roberto Gomes Azevedo1, Miguel Angel Claros Paz1, 1Anhanguera University, S~ao Paulo, Brazil; 2FAMA College, Mineiros, Brazil. Contact e-mail: [email protected] Background: Thyroid hormones have many effects on development,
growth and fundamentally modulate all metabolic pathways through changes in oxygen consumption, as well as changes in the metabolism of proteins, lipids, carbohydrates and vitamins as
Poster Presentations: Tuesday, July 26, 2016
2.94). Conclusions: Elevated plasma tau is associated with neuroimaging measures of neurodegeneration and with worse memory performance in a population based cohort. Additional studies are needed to verify these findings and further elucidate the connection between plasma tau levels, neurodegeneration, and cognition. P3-153
MULTILEVEL ANALYSIS OF BIOMARKER POOL FOR ALZHEIMER’S DISEASE RISK IN A NORTH INDIAN POPULATION 1
1
2
Ritushree Kukreti , Puneet Talwar , Suman Kushwaha , Rachna Agarwal2, 1CSIR-Institute of Genomics and Integrative Biology, Delhi, India; 2Institute of Human Behaviour and Allied Sciences, Delhi, India. Contact e-mail: [email protected] Background: Alzheimer’s disease (AD) is a progressive neurode-
generative disease with complex pathophysiology and multifactorial etiology. Here, we aim to examine the gene-environment interaction with reference to genetic variants from AD associated genes, blood biomarkers, clinical variables and demographic factors as predictors of AD risk. Methods: We performed identification of biomarker pool in case-control study involving 108 AD cases and 159 non-demented healthy controls to examine association among multiple biomarkers. Results: APOE genotyping revealed that e4 allele frequency was significantly high (p value¼0.0001, OR¼2.66, 95%CI¼1.58-4.46) in AD as compared to controls whereas APOE e2 (p: 0.043, OR¼0.29, CI¼0.07-1.10) was overrepresented in controls. In biochemical assays, a significant difference (p<0.05) in levels of copper, free copper, zinc, iron, epidermal growth factor receptor (EGFR), copper/zinc and leptin was observed between AD patients and controls. Then, we created the AD risk-score(ADRS) as linear combination of seven candidate markers involving age, APOE e4 allele and levels of iron, leptin, EGFR, albumin and Cu/Zn ratio. The area under the ROC curve of the combined ADRS panel for predicting AD risk was higher (AUC¼0.83, p<0.0001, 95%CI¼0.77-0.89), as compared to individual parameters alone. The sensitivity and specificity was found to be 67.8% and 83.7% respectively. Conclusions: The findings provide evidence on the multifactorial etiology of AD and demonstrated ability of a panel involving seven biomarkers to discriminate AD cases from non-demented healthy controls. P3-154
PLASMA BIOMARKERS OF NEOCORTICAL AMYLOID BURDEN: AN IN-DEPTH PLASMA PROFILE USING LC-MS
Nicholas J. Ashton1,2, Alejo Narvardo3, Steven Lynham2, Malcolm Ward2, Veer Gupta4,5, Pratishtha Chatterjee6,7, Kathryn Goozee4,6,8,9,10, McCusker KARVIAH Research Group11, Eugene Hone4,5, Steve Pedrini4,5, Stephanie R. Rainey-Smith4,12, Simon M. Laws4,5, Ashley I. Bush5,13,14, Christopher C. Rowe14,15, David Ames14,16,17, Victor L. Villemagne14,18, Colin L. Masters13,14, AIBL Research Group14, Simon Lovestone3, Ralph N. Martins4,5,9,12,14, Abdul Hye1,2, 1NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, United Kingdom; 2 Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom; 3University of Oxford, Oxford, United Kingdom; 4Edith Cowan University, Perth, Australia; 5Cooperative Research Centre for Mental Health, Melbourne, Australia; 6KaRa Institute of Neurological Diseases, Sydney, Australia; 7Macquarie University, Sydney, Australia; 8Faculty of Medicine and Health Sciences, Macquarie University, Sydney, Australia; 9School of Psychiatry and Clinical Neurosciences, University of Western Australia, Perth, Australia; 10The
Anglican Retirement Villages, Sydney, Australia; 11McCusker KARVIAH Research Group, Perth, Australia; 12Sir James McCusker Alzheimer’s Disease Research Unit (Hollywood Private Hospital), Perth, Australia; 13 The Florey Institute of Neuroscience and Mental Health, Melbourne, Australia; 14AIBL Research Group, Perth and Melbourne, Australia; 15 Austin Health, Melbourne, Australia; 16The University of Melbourne, Melbourne, Australia; 17National Ageing Research Institute, Melbourne, Australia; 18Department of Molecular Imaging and Therapy, Centre for PET, Austin Health, Heidelberg, Australia. Contact e-mail: nicholas.1. [email protected] Background: Neocortical amyloid burden (NAB) is an important risk factor for Alzheimer’s disease (AD) that precedes the onset of clinical symptoms. It has become critical to identify individuals at early stages of NAB deposition to recruit into clinical trials of disease-modifying therapeutics. Blood-based biomarkers predicting NAB would have great utility for enrichment of AD clinical trials, including large-scale prevention trials. Despite this, only a handful of studies have investigated plasma biomarkers of NAB (Thambisetty et al; Burnham et al; Kiddle et al), with one study utilising Mass Spectrometry (MS) (Ashton et al). MS has several advantages as a discovery tool over panel-based assays however its limited sensitivity and protein coverage have been a restricting factor. Here, we present an in-depth MS-based screen of cognitively normal (CN) participants with varying degree of NAB. The objective was to identify a peripheral signature of AD pathology which precedes clinical manifestation. Methods: A proteomic workflow combining immunodepletion, isobaric peptide labelling and Isoelectric focusing (IEF) was established as a sensitive and robust strategy for in-depth plasma exploration compared with other proteomic methodologies (unpublished). Protein identification and relative quantitation was performed by MS (Orbitrap Velos). This methodology was applied to n¼297 CN participants from the AIBL and KARVIAH cohorts. All participants underwent PET amyloid imaging at time of sampling with n¼187 having subsequent imaging at multiple time-points. Linear Models, Discriminant Analysis and Support Vector Machines were performed to establish a cross-sectional and longitudinal proteomic model of elevated NAB. Results: A refined proteomic strategy has demonstrated a reproducible workflow that can profile >1000 plasma proteins, accurately detecting low picogram levels (unpublished). In addition to increased dynamic range, proteins indicative of the central nervous system (CNS) such as myelin basic protein and neurogranin are routinely observed. This discovery methodology has allowed the generation of a novel prediction model for both baseline and prospective NAB. Conclusions: An in-depth MS-based workflow has confirmed CNS proteins are readily measureable in the periphery, which has enabled the most detailed proteomic screen of AD pathology to date. Further replication of these putative markers will be needed although this additional evidence illustrates the potential use of a blood-based strategy in AD.
P3-155
THYROID HORMONES AND ALZHEIMER’S DISEASE
Gustavo A. A. Santos1, Paulo Celso Pardi2, Niraldo Paulino1, Roberto Gomes Azevedo1, Miguel Angel Claros Paz1, 1Anhanguera University, S~ao Paulo, Brazil; 2FAMA College, Mineiros, Brazil. Contact e-mail: [email protected] Background: Thyroid hormones have many effects on development,
growth and fundamentally modulate all metabolic pathways through changes in oxygen consumption, as well as changes in the metabolism of proteins, lipids, carbohydrates and vitamins as