PubMed

Related Articles Altered branched chain amino acid metabolism: toward a unifying cardiometabolic hypothesis. Curr Opin Cardiol. 2018 Jul 09;: Authors: Tobias DK, Mora S, Verma S, Lawler PR Abstract PURPOSE OF REVIEW: Atherosclerotic cardiovascular disease (CVD) and type II diabetes (T2D) share common etiologic pathways that may long precede the development of clinically evident disease. Early identification of risk markers could support efforts to individualize risk prediction and improve the efficacy of primary prevention, as well as uncover novel therapeutic targets. RECENT FINDINGS: Altered metabolism of branched-chain amino acids (BCAAs), and their subsequent accumulation in circulation, may precede the development of insulin resistance and clinically manifest cardiometabolic diseases. BCAAs - the essential amino acids leucine, isoleucine and valine - likely promote insulin resistance through activation of mammalian target of rapamycin complex 1. Epidemiologic studies demonstrate robust associations between BCAAs and incident T2D, and Mendelian randomization supports a potentially causal relationship. More recently, there is emerging evidence that BCAAs are also associated with incident atherosclerotic CVD, possibly mediated by the development of T2D. SUMMARY: In this article, we review the biochemistry of BCAAs, their potential contribution to cardiometabolic risk, the available evidence from molecular epidemiologic studies to date, and, finally, consider future research and clinical directions. Overall, BCAAs represent a promising emerging target for risk stratification and possible intervention, to support efforts to mitigate the burden of cardiometabolic disease in the population. PMID: 29994805 [PubMed - as supplied by publisher]

Related Articles MixProTool: A Powerful and Comprehensive Web Tool for Analyzing and Visualizing Multigroup Proteomics Data. J Comput Biol. 2018 Jul 11;: Authors: Wang S, Zheng W, Hu L, Gong M, Yang H Abstract Deciphering and visualizing proteomics data are a big challenge for high-throughput proteomics research. In this work, we develop a free interactive web software platform, MixProTool, for processing multigroup proteomics data sets. This tool provides integrated data analysis workflow, including quality control assessment, normalization, soft independent modeling of class analogy, statistics, gene ontology enrichment, and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. This software is also highly compatible with the identification and quantification results of various frequently used search engines, such as MaxQuant, Proteome Discoverer, or Mascot. Moreover, all analyzed results can be visualized as vector graphs and tables for further analysis. MixProTool can be conveniently operated by users, even those without bioinformatics training, and it is extremely useful for mining the most relevant features among different samples. MixProTool is deployed at the public shinyapps io server. PMID: 29993281 [PubMed - as supplied by publisher]

Related Articles Toward Reproducible Results from Targeted Metabolomic Studies: Perspectives for Data Pre-Processing and a Basis for Analytic Pipeline Development. Curr Top Med Chem. 2018 Jul 11;: Authors: Gross T, Mapstone M, Miramontes R, Padilla R, Cheema AK, Macciardi F, Federoff HJ, Fiandaca MS Abstract Contemporary metabolomics experiments generate a rich array of complex high-dimensional data. Consequently, there have been concurrent efforts to develop methodological standards and analytical workflows to streamline the generation of meaningful biochemical and clinical inferences from raw data generated using an analytical platform like mass spectrometry. While such considerations have been frequently addressed in untargeted metabolomics (i.e., the broad survey of all distinguishable metabolites within a sample of interest), this methodological scrutiny has seldom been applied to data generated using commercial, targeted metabolomics kits. We suggest that this may, in part, account for past and more recent incomplete replications of previously specified biomarker panels. Herein, we identify common impediments challenging the analysis of raw, targeted metabolomic abundance data from a commercial kit and review methods to remedy these issues. In doing so, we propose an analytical pipeline suitable for the pre-processing of data for downstream biomarker discovery. Operational and statistical considerations for integrating targeted data sets across experimental sites and analytical batches are discussed, as are best practices for developing predictive models relating pre-processed metabolomic data to associated phenotypic information. PMID: 29992885 [PubMed - as supplied by publisher]

Related Articles Intervention and Observational Trials Are Complementary in Metabolomics: Diabetes and the Oral Glucose Tolerance Test. Curr Top Med Chem. 2018 Jul 11;: Authors: Gonzalez-Dominguez A, Lechuga-Sancho AM, Gonzalez-Dominguez R Abstract Observational experimental designs are usually employed in metabolomics to elucidate pathological mechanisms underlying disease development and to discover candidate biomarkers for diagnosis. However, intervention trials can also be a suitable starting point before performing a validation study in lager epidemiological cohorts, with a great potential in personalized medicine to investigate how different patients respond to similar stimuli. In the present work, we provide a review of the literature on the application of metabolomics to investigate metabolic alterations associated with diabetes, the diabetes predisposing state of insulin resistance and the oral glucose tolerance test as a case study to demonstrate the complementarity of observational and interventional study designs. PMID: 29992883 [PubMed - as supplied by publisher]

Related Articles An Overview of Metabolic Phenotyping in Blood Pressure Research. Curr Hypertens Rep. 2018 Jul 10;20(9):78 Authors: Tzoulaki I, Iliou A, Mikros E, Elliott P Abstract PURPOSE OF THE REVIEW: This review presents the analytical techniques, processing and analytical steps used in metabolomics phenotyping studies, as well as the main results from epidemiological studies on the associations between metabolites and high blood pressure. RECENT FINDINGS: A variety of metabolomic approaches have been applied to a range of epidemiological studies to uncover the pathophysiology of high blood pressure. Several pathways have been suggested in relation to blood pressure including the possible role of the gut microflora, inflammatory, oxidative stress, and lipid pathways. Metabolic changes have also been identified associated with blood pressure lowering effects of diets high in fruits and vegetables and low in meat intake. However, the current body of literature on metabolic profiling and blood pressure is still in its infancy, not fully consistent and requires careful interpretation. Metabolic phenotyping is a promising approach to uncover metabolic pathways associated with high blood pressure and throw light into the complex pathophysiology of hypertension. PMID: 29992526 [PubMed - in process]

Related Articles Age at diagnosis and prognosis among prostate cancer patients treated with radiotherapy: evidenced from three independent cohort studies. Ann Oncol. 2018 Jul 09;: Authors: Dong X, Ma G, Chen F PMID: 29992296 [PubMed - as supplied by publisher]

Related Articles Metabolic Profiles of Propofol and Fospropofol: Clinical and Forensic Interpretative Aspects. Biomed Res Int. 2018;2018:6852857 Authors: Dinis-Oliveira RJ Abstract Propofol is an intravenous short-acting anesthetic widely used to induce and maintain general anesthesia and to provide procedural sedation. The potential for propofol dependency and abuse has been recognized, and several cases of accidental overdose and suicide have emerged, mostly among the health professionals. Different studies have demonstrated an unpredictable interindividual variability of propofol pharmacokinetics and pharmacodynamics with forensic and clinical adverse relevant outcomes (e.g., pronounced respiratory and cardiac depression), namely, due to polymorphisms in the UDP-glucuronosyltransferase and cytochrome P450 isoforms and drugs administered concurrently. In this work the pharmacokinetics of propofol and fospropofol with particular focus on metabolic pathways is fully reviewed. It is concluded that knowing the metabolism of propofol may lead to the development of new clues to help further toxicological and clinical interpretations and to reduce serious adverse reactions such as respiratory failure, metabolic acidosis, rhabdomyolysis, cardiac bradyarrhythmias, hypotension and myocardial failure, anaphylaxis, hypertriglyceridemia, renal failure, hepatomegaly, hepatic steatosis, acute pancreatitis, abuse, and death. Particularly, further studies aiming to characterize polymorphic enzymes involved in the metabolic pathway, the development of additional routine forensic toxicological analysis, and the relatively new field of ''omics" technology, namely, metabolomics, can offer more in explaining the unpredictable interindividual variability. PMID: 29992157 [PubMed - in process]

Related Articles Diagnosis of major depressive disorder based on changes in multiple plasma neurotransmitters: a targeted metabolomics study. Transl Psychiatry. 2018 Jul 10;8(1):130 Authors: Pan JX, Xia JJ, Deng FL, Liang WW, Wu J, Yin BM, Dong MX, Chen JJ, Ye F, Wang HY, Zheng P, Xie P Abstract Major depressive disorder (MDD) is a debilitating psychiatric illness. However, there is currently no objective laboratory-based diagnostic tests for this disorder. Although, perturbations in multiple neurotransmitter systems have been implicated in MDD, the biochemical changes underlying the disorder remain unclear, and a comprehensive global evaluation of neurotransmitters in MDD has not yet been performed. Here, using a GC-MS coupled with LC-MS/MS-based targeted metabolomics approach, we simultaneously quantified the levels of 19 plasma metabolites involved in GABAergic, catecholaminergic, and serotonergic neurotransmitter systems in 50 first-episode, antidepressant drug-naïve MDD subjects and 50 healthy controls to identify potential metabolite biomarkers for MDD (training set). Moreover, an independent sample cohort comprising 49 MDD patients, 30 bipolar disorder (BD) patients and 40 healthy controls (testing set) was further used to validate diagnostic generalizability and specificity of these candidate biomarkers. Among the 19 plasma neurotransmitter metabolites examined, nine were significantly changed in MDD subjects. These metabolites were mainly involved in GABAergic, catecholaminergic and serotonergic systems. The GABAergic and catecholaminergic had better diagnostic value than serotonergic pathway. A panel of four candidate plasma metabolite biomarkers (GABA, dopamine, tyramine, kynurenine) could distinguish MDD subjects from health controls with an AUC of 0.968 and 0.953 in the training and testing set, respectively. Furthermore, this panel distinguished MDD subjects from BD subjects with high accuracy. This study is the first to globally evaluate multiple neurotransmitters in MDD plasma. The altered plasma neurotransmitter metabolite profile has potential differential diagnostic value for MDD. PMID: 29991685 [PubMed - in process]

Related Articles Separation of circadian- and behavior-driven metabolite rhythms in humans provides a window on peripheral oscillators and metabolism. Proc Natl Acad Sci U S A. 2018 Jul 10;: Authors: Skene DJ, Skornyakov E, Chowdhury NR, Gajula RP, Middleton B, Satterfield BC, Porter KI, Van Dongen HPA, Gaddameedhi S Abstract Misalignment between internal circadian rhythmicity and externally imposed behavioral schedules, such as occurs in shift workers, has been implicated in elevated risk of metabolic disorders. To determine underlying mechanisms, it is essential to assess whether and how peripheral clocks are disturbed during shift work and to what extent this is linked to the central suprachiasmatic nuclei (SCN) pacemaker and/or misaligned behavioral time cues. Investigating rhythms in circulating metabolites as biomarkers of peripheral clock disturbances may offer new insights. We evaluated the impact of misaligned sleep/wake and feeding/fasting cycles on circulating metabolites using a targeted metabolomics approach. Sequential plasma samples obtained during a 24-h constant routine that followed a 3-d simulated night-shift schedule, compared with a simulated day-shift schedule, were analyzed for 132 circulating metabolites. Nearly half of these metabolites showed a 24-h rhythmicity under constant routine following either or both simulated shift schedules. However, while traditional markers of the circadian clock in the SCN-melatonin, cortisol, and PER3 expression-maintained a stable phase alignment after both schedules, only a few metabolites did the same. Many showed reversed rhythms, lost their rhythms, or showed rhythmicity only under constant routine following the night-shift schedule. Here, 95% of the metabolites with a 24-h rhythmicity showed rhythms that were driven by behavioral time cues externally imposed during the preceding simulated shift schedule rather than being driven by the central SCN circadian clock. Characterization of these metabolite rhythms will provide insight into the underlying mechanisms linking shift work and metabolic disorders. PMID: 29991600 [PubMed - as supplied by publisher]

Related Articles Early Diagnosis of Sepsis: Is an Integrated Omics Approach the Way Forward? Mol Diagn Ther. 2017 Oct;21(5):525-537 Authors: Langley RJ, Wong HR Abstract Sepsis remains one of the leading causes of death in the USA and it is expected to get worse as the population ages. Moreover, the standard of care, which recommends aggressive treatment with appropriate antibiotics, has led to an increase in multiple drug-resistant organisms. There is a dire need for the development of new antibiotics, improved antibiotic stewardship, and therapies that treat the host response. Development of new sepsis therapeutics has been a disappointment as no drugs are currently approved to treat the various complications from sepsis. Much of the failure has been blamed on animal models that do not accurately reflect the course of the disease. However, recent improvements in metabolomic, transcriptomic, genomic, and proteomic platforms have allowed for a broad-spectrum look at molecular changes in the host response using clinical samples. Integration of these multi-omic datasets allows researchers to perform systems biology approaches to identify novel pathophysiology of the disease. In this review, we highlight what is currently known about sepsis and how integrative omics has identified new diagnostic and predictive models of sepsis as well as novel mechanisms. These changes may improve patient care as well as guide future preclinical analysis of sepsis. PMID: 28624903 [PubMed - indexed for MEDLINE]

22 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2018/07/11PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

22 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2018/07/11PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

17 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2018/07/10PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

Proteome profiling in the hippocampus, medial prefrontal cortex, and striatum of aging rat. Exp Gerontol. 2018 Jul 04;: Authors: Hamezah HS, Durani LW, Yanagisawa D, Ibrahim NF, Aizat WM, Bellier JP, Makpol S, Ngah WZW, Damanhuri HA, Tooyama I Abstract Decrease in multiple functions occurs in the brain with aging, all of which can contribute to age-related cognitive and locomotor impairments. Brain atrophy specifically in hippocampus, medial prefrontal cortex (mPFC), and striatum, can contribute to this age-associated decline in function. Our recent metabolomics analysis showed age-related changes in these brain regions. To further understand the aging processes, analysis using a proteomics approach was carried out. This study was conducted to identify proteome profiles in the hippocampus, mPFC, and striatum of 14-, 18-, 23-, and 27-month-old rats. Proteomics analysis using ultrahigh performance liquid chromatography coupled with Q Exactive HF Orbitrap mass spectrometry identified 1074 proteins in the hippocampus, 871 proteins in the mPFC, and 241 proteins in the striatum. Of these proteins, 97 in the hippocampus, 25 in mPFC, and 5 in striatum were differentially expressed with age. The altered proteins were classified into three ontologies (cellular component, molecular function, and biological process) containing 44, 38, and 35 functional groups in the hippocampus, mPFC, and striatum, respectively. Most of these altered proteins participate in oxidative phosphorylation (e.g. cytochrome c oxidase and ATP synthase), glutathione metabolism (e.g. peroxiredoxins), or calcium signaling pathway (e.g. protein S100B and calmodulin). The most prominent changes were observed in the oldest animals. These results suggest that alterations in oxidative phosphorylation, glutathione metabolism, and calcium signaling pathway are involved in cognitive and locomotor impairments in aging. PMID: 29981398 [PubMed - as supplied by publisher]

Predictors of Treatment Response in Rheumatoid Arthritis. Joint Bone Spine. 2018 Jul 04;: Authors: Lequerré T, Rottenberg P, Derambure C, Cosette P, Vittecoq O Abstract The expanding array of drugs available for treating rheumatoid arthritis is creating challenges in drug selection for the individual patient. The identification of biomarkers that predict the treatment response prior to drug exposure is therefore a current priority. This new approach, known as theranostics, is a component of personalized medicine, which involves selecting the management strategies that are most effective for a given patient at a given point in time. Antibodies to citrullinated peptides, rheumatoid factor, and the interferon signature are the most robust and best validated biomarkers identified to date. Matrices containing clinical or laboratory parameters of diagnostic or prognostic relevance may help to select the best treatment for the individual patient. Furthermore, the development of large-scale approaches requiring no a priori knowledge, such as functional genomics and metabolomics, hold considerable promise, despite persistent difficulties in replicating findings. The complexity of the treatment response in a given patient and substantial variability across patients suggest that biomarkers may be more helpful in combination than singly. The objectives of this review article are to discuss the approaches used to identify theranostic biomarkers and to present an overview of currently available biomarkers and of their performance in everyday clinical practice. However, the range of biomarkers suitable for use in daily practice remains extremely narrow. PMID: 29981377 [PubMed - as supplied by publisher]

Metabolomic Profiling of rats'Urine After Oral Administration of the Prescription Antipyretic Hao Jia Xu Re Qing Granules by UPLC/Q-TOF-MS. Biomed Chromatogr. 2018 Jul 07;:e4332 Authors: Yu CQ, Chen JP, Zhong YM, Zhong XL, Tang CP, Yang Y, Lin HQ Abstract Hao Jia Xu Re Qing Granules (HJ), is an effective clinically used antipyretic based on Traditional Chinese Medicine (TCM). Although its antipyretic therapeutic effectiveness is obvious, its therapeutic mechanism has not been comprehensively explored yet. In this research, we first identified potential biomarkers which may be relevant for the antipyretic effect of HJ based on urine metabolomics using Ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS). A rat model of fever was established using the yeast-induced febrile response. Total-ion-current metabolic profiles of different groups were acquired and the data were processed by multivariate statistical analysis-partial least-squares discriminant analysis (PLSDA). As envisioned, the results revealed changes of urine metabolites related to the antipyretic effect. fourteen potential biomarkers were selected from the urine samples based on the results of Student's t-test, "shrinkaget", variable importance in projection (VIP), and PLSDA. N-acetylleucine, kynurenic acid, indole-3-ethanol, nicotinuric acid, pantothenic acid, and tryptophan were the most significant biomarkers found in the urine samples, and may be crucially related to the antipyretic effect of HJ. Consequently, we propose the hypothesis that the significant antipyretic effect the HJ may be related to the inhibition of tryptophan metabolism. This research thus provides strong theoretical support and further direction to explain the antipyretic mechanism of HJ, laying the foundation for future studies. PMID: 29981286 [PubMed - as supplied by publisher]

Related Articles Transformed Root Culture: From Genetic Transformation to NMR-Based Metabolomics. Methods Mol Biol. 2018;1815:457-474 Authors: Marchev AS, Yordanova ZP, Georgiev MI Abstract Hairy root (HR) culture is considered as "green factory" for mass production of bioactive molecules with pharmaceutical relevance. As such, HR culture has an immense potential as a valuable platform to elucidate biosynthetic pathways and physiological processes, generate recombinant therapeutic proteins, assist molecular breeding, and enhance phytoremediation efforts. However, some plant species appear recalcitrant to the classical Agrobacterium rhizogenes transformation techniques. Sonication-assisted Agrobacterium-mediated transformation (SAArT) is a highly effective method to deliver bacteria to target plant tissues that includes exposure of the explants to short periods of ultrasound in the presence of the bacteria.Nuclear magnetic resonance (NMR)-based metabolomics is one of the most powerful and suitable platforms for identifying and obtaining structural information on a wide range of compounds with a high analytical precision. In terms of plant science, NMR metabolomics is used to determine the phytochemical variations of medicinal plants or commercial cultivars in certain environments and conditions, including biotic stress and plant biotic interaction, structural determination of natural products, quality control of herbal drugs or dietary supplements, and comparison of metabolite differences between plants and their respective in vitro cultures.In this chapter, we attempt to summarize our knowledge and expertise in induction of hairy roots from rare and recalcitrant plant species by SAArT technique and further methodology for extraction of secondary metabolites of moderate to high polarity and their identification by using NMR-based metabolomics. PMID: 29981142 [PubMed - in process]

Related Articles Analysis of Terpenoid Indole Alkaloids, Carotenoids, Phytosterols, and NMR-Based Metabolomics for Catharanthus roseus Cell Suspension Cultures. Methods Mol Biol. 2018;1815:437-455 Authors: Saiman MZ, Mustafa NR, Verpoorte R Abstract The plant Catharanthus roseus is a rich source of terpenoid indole alkaloids (TIA). Some of the TIA are important as antihypertensive (ajmalicine) and anticancer (vinblastine and vincristine) drugs. However, production of the latter is very low in the plant. Therefore, in vitro plant cell cultures have been considered as a potential supply of these chemicals or their precursors. Some monomeric alkaloids can be produced by plant cell cultures, but not on a level feasible for commercialization, despite extensive studies on this plant that deepened the understanding of the TIA biosynthesis and its regulation. In order to analyze the metabolites in C. roseus cell cultures, this chapter presents the method of TIA, carotenoids, and phytosterols analyses. Furthermore, an NMR-based metabolomics approach to study C. roseus cell culture is described. PMID: 29981141 [PubMed - in process]

Related Articles An Introduction to Plant Tissue Culture: Advances and Perspectives. Methods Mol Biol. 2018;1815:3-13 Authors: Loyola-Vargas VM, Ochoa-Alejo N Abstract Plant tissue culture techniques are the most frequently used biotechnological tools for basic and applied purposes ranging from investigation on plant developmental processes, functional gene studies, commercial plant micropropagation, generation of transgenic plants with specific industrial and agronomical traits, plant breeding and crop improvement, virus elimination from infected materials to render high-quality healthy plant material, preservation and conservation of germplasm of vegetative propagated plant crops, and rescue of threatened or endangered plant species. Additionally, plant cell and organ cultures are of interest for the production of secondary metabolites of industrial and pharmaceutical interest. New technologies, such as the genome editing ones combined with tissue culture and Agrobacterium tumefaciens infection, are currently promising alternatives for the highly specific genetic manipulation of interesting agronomical or industrial traits in crop plants. Application of omics (genomics, transcriptomics, and proteomics) to plant tissue culture will certainly help to unravel complex developmental processes such as organogenesis and somatic embryogenesis, which will probably enable to improve the efficiency of regeneration protocols for recalcitrant species. Additionally, metabolomics applied to tissue culture will facilitate the extraction and characterization of complex mixtures of natural plant products of industrial interest. General and specific aspects and applications of plant tissue culture and the advances and perspectives are described in this edition. PMID: 29981111 [PubMed - in process]

Related Articles The EMIF-AD Multimodal Biomarker Discovery study: design, methods and cohort characteristics. Alzheimers Res Ther. 2018 Jul 06;10(1):64 Authors: Bos I, Vos S, Vandenberghe R, Scheltens P, Engelborghs S, Frisoni G, Molinuevo JL, Wallin A, Lleó A, Popp J, Martinez-Lage P, Baird A, Dobson R, Legido-Quigley C, Sleegers K, Van Broeckhoven C, Bertram L, Ten Kate M, Barkhof F, Zetterberg H, Lovestone S, Streffer J, Visser PJ Abstract BACKGROUND: There is an urgent need for novel, noninvasive biomarkers to diagnose Alzheimer's disease (AD) in the predementia stages and to predict the rate of decline. Therefore, we set up the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery (EMIF-AD MBD) study. In this report we describe the design of the study, the methods used and the characteristics of the participants. METHODS: Participants were selected from existing prospective multicenter and single-center European studies. Inclusion criteria were having normal cognition (NC) or a diagnosis of mild cognitive impairment (MCI) or AD-type dementia at baseline, age above 50 years, known amyloid-beta (Aβ) status, availability of cognitive test results and at least two of the following materials: plasma, DNA, magnetic resonance imaging (MRI) or cerebrospinal fluid (CSF). Targeted and untargeted metabolomic and proteomic analyses were performed in plasma, and targeted and untargeted proteomics were performed in CSF. Genome-wide SNP genotyping, next-generation sequencing and methylation profiling were conducted in DNA. Visual rating and volumetric measures were assessed on MRI. Baseline characteristics were analyzed using ANOVA or chi-square, rate of decline analyzed by linear mixed modeling. RESULTS: We included 1221 individuals (NC n = 492, MCI n = 527, AD-type dementia n = 202) with a mean age of 67.9 (SD 8.3) years. The percentage Aβ+ was 26% in the NC, 58% in the MCI, and 87% in the AD-type dementia groups. Plasma samples were available for 1189 (97%) subjects, DNA samples for 929 (76%) subjects, MRI scans for 862 (71%) subjects and CSF samples for 767 (63%) subjects. For 759 (62%) individuals, clinical follow-up data were available. In each diagnostic group, the APOE ε4 allele was more frequent amongst Aβ+ individuals (p < 0.001). Only in MCI was there a difference in baseline Mini Mental State Examination (MMSE) score between the A groups (p < 0.001). Aβ+ had a faster rate of decline on the MMSE during follow-up in the NC (p < 0.001) and MCI (p < 0.001) groups. CONCLUSIONS: The characteristics of this large cohort of elderly subjects at various cognitive stages confirm the central roles of Aβ and APOE ε4 in AD pathogenesis. The results of the multimodal analyses will provide new insights into underlying mechanisms and facilitate the discovery of new diagnostic and prognostic AD biomarkers. All researchers can apply for access to the EMIF-AD MBD data by submitting a research proposal via the EMIF-AD Catalog. PMID: 29980228 [PubMed - in process]