Dataset Information

Metabolic network failures in Alzheimer's disease: A biochemical road map.

ABSTRACT: INTRODUCTION:The Alzheimer's Disease Research Summits of 2012 and 2015 incorporated experts from academia, industry, and nonprofit organizations to develop new research directions to transform our understanding of Alzheimer's disease (AD) and propel the development of critically needed therapies. In response to their recommendations, big data at multiple levels are being generated and integrated to study network failures in disease. We used metabolomics as a global biochemical approach to identify peripheral metabolic changes in AD patients and correlate them to cerebrospinal fluid pathology markers, imaging features, and cognitive performance. METHODS:Fasting serum samples from the Alzheimer's Disease Neuroimaging Initiative (199 control, 356 mild cognitive impairment, and 175 AD participants) were analyzed using the AbsoluteIDQ-p180 kit. Performance was validated in blinded replicates, and values were medication adjusted. RESULTS:Multivariable-adjusted analyses showed that sphingomyelins and ether-containing phosphatidylcholines were altered in preclinical biomarker-defined AD stages, whereas acylcarnitines and several amines, including the branched-chain amino acid valine and ?-aminoadipic acid, changed in symptomatic stages. Several of the analytes showed consistent associations in the Rotterdam, Erasmus Rucphen Family, and Indiana Memory and Aging Studies. Partial correlation networks constructed for A?1-42, tau, imaging, and cognitive changes provided initial biochemical insights for disease-related processes. Coexpression networks interconnected key metabolic effectors of disease. DISCUSSION:Metabolomics identified key disease-related metabolic changes and disease-progression-related changes. Defining metabolic changes during AD disease trajectory and its relationship to clinical phenotypes provides a powerful roadmap for drug and biomarker discovery.

SUBMITTER: Toledo JB

PROVIDER: S-EPMC5866045 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

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Metabolic network failures in Alzheimer's disease: A biochemical road map.

Toledo Jon B JB Arnold Matthias M Kastenmüller Gabi G Chang Rui R Baillie Rebecca A RA Han Xianlin X Thambisetty Madhav M Tenenbaum Jessica D JD Suhre Karsten K Thompson J Will JW John-Williams Lisa St LS MahmoudianDehkordi Siamak S Rotroff Daniel M DM Jack John R JR Motsinger-Reif Alison A Risacher Shannon L SL Blach Colette C Lucas Joseph E JE Massaro Tyler T Louie Gregory G Zhu Hongjie H Dallmann Guido G Klavins Kristaps K Koal Therese T Kim Sungeun S Nho Kwangsik K Shen Li L Casanova Ramon R Varma Sudhir S Legido-Quigley Cristina C Moseley M Arthur MA Zhu Kuixi K Henrion Marc Y R MYR van der Lee Sven J SJ Harms Amy C AC Demirkan Ayse A Hankemeier Thomas T van Duijn Cornelia M CM Trojanowski John Q JQ Shaw Leslie M LM Saykin Andrew J AJ Weiner Michael W MW Doraiswamy P Murali PM Kaddurah-Daouk Rima R

Alzheimer's & dementia : the journal of the Alzheimer's Association 20170322 9

<h4>Introduction</h4>The Alzheimer's Disease Research Summits of 2012 and 2015 incorporated experts from academia, industry, and nonprofit organizations to develop new research directions to transform our understanding of Alzheimer's disease (AD) and propel the development of critically needed therapies. In response to their recommendations, big data at multiple levels are being generated and integrated to study network failures in disease. We used metabolomics as a global biochemical approach t ...[more]

PMID: 28341160

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Project description:Roadways pose serious threats to animal populations. The installation of roadway mitigation measures is becoming increasingly common, yet studies that rigorously evaluate the effectiveness of these conservation tools remain rare. A highway expansion project in Ontario, Canada included exclusion fencing and ecopassages as mitigation measures designed to offset detrimental effects to one of the most imperial groups of vertebrates, reptiles. Taking a multispecies approach, we used a Before-After-Control-Impact study design to compare reptile abundance on the highway before and after mitigation at an Impact site and a Control site from 1 May to 31 August in 2012 and 2013. During this time, radio telemetry, wildlife cameras, and an automated PIT-tag reading system were used to monitor reptile movements and use of ecopassages. Additionally, a willingness to utilize experiment was conducted to quantify turtle behavioral responses to ecopassages. We found no difference in abundance of turtles on the road between the un-mitigated and mitigated highways, and an increase in the percentage of both snakes and turtles detected dead on the road post-mitigation, suggesting that the fencing was not effective. Although ecopassages were used by reptiles, the number of crossings through ecopassages was lower than road-surface crossings. Furthermore, turtle willingness to use ecopassages was lower than that reported in previous arena studies, suggesting that effectiveness of ecopassages may be compromised when alternative crossing options are available (e.g., through holes in exclusion structures). Our rigorous evaluation of reptile roadway mitigation demonstrated that when exclusion structures fail, the effectiveness of population connectivity structures is compromised. Our project emphasizes the need to design mitigation measures with the biology and behavior of the target species in mind, to implement mitigation designs in a rigorous fashion, and quantitatively evaluate road mitigation to ensure allow for adaptive management and optimization of these increasingly important conservation tools.

Dataset Information

Metabolic network failures in Alzheimer's disease: A biochemical road map.

Publications

Metabolic network failures in Alzheimer's disease: A biochemical road map.

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