Metabolite Profiling of Alzheimer's Disease Cerebrospinal Fluid

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressive loss of cognitive functions. Today the diagnosis of AD relies on clinical evaluations and is only late in the disease. Biomarkers for early detection of the underlying neuropathological changes are still lacking and the biochemical pathways leading to the disease are still not completely understood. The aim of this study was to identify the metabolic changes resulting from the disease phenotype by a thorough and systematic metabolite profiling approach. For this purpose CSF samples from 79 AD patients and 51 healthy controls were analyzed by gas and liquid chromatography-tandem mass spectrometry (GC-MS and LC-MS/MS) in conjunction with univariate and multivariate statistical analyses. In total 343 different analytes have been identified. Significant changes in the metabolite profile of AD patients compared to healthy controls have been identified. Increased cortisol levels seemed to be related to the progression of AD and have been detected in more severe forms of AD. Increased cysteine associated with decreased uridine was the best paired combination to identify light AD (MMSE>22) with specificity and sensitivity above 75%. In this group of patients, sensitivity and specificity above 80% were obtained for several combinations of three to five metabolites, including cortisol and various amino acids, in addition to cysteine and uridine

A functional analysis of mouse models of cardiac disease through metabolic profiling.

Since the completion of the human and mouse genomes, the focus in mammalian biology has been on assessing gene function. Tools are needed for assessing the phenotypes of the many mouse models that are now being generated, where genes have been "knocked out," "knocked in," or mutated, so that gene expression can be understood in its biological context. Metabolic profiling of cardiac tissue through high resolution NMR spectroscopy in conjunction with multivariate statistics has been used to classify mouse models of cardiac disease. The data sets included metabolic profiles from mouse models of Duchenne muscular dystrophy, two models of cardiac arrhythmia, and one of cardiac hypertrophy. The metabolic profiles demonstrate that the strain background is an important component of the global metabolic phenotype of a mouse, providing insight into how a given gene deletion may result in very different responses in diverse populations. Despite these differences associated with strain, multivariate statistics were capable of separating each mouse model from its control strain, demonstrating that metabolic profiles could be generated for each disease. Thus, this approach is a rapid method of phenotyping mouse models of disease

Environmental influences on the replenishment of lizardfish\ud (family Synodontidae) in Caribbean Panama

Lizardfish (family Synodontidae) are little studied despite their potentially important predatory role in epibenthic coral reef communities. The present study documented the temporal and spatial larval supply patterns of five Caribbean lizardfish species together with environmental variables (solar radiation, rainfall, water temperature, onshore-offshore winds, alongshore winds and wind-induced turbulence) to examine: (1) whether species within the same family respond differently to their developmental environment and (2) if larval supply in year-round warm waters is influenced by climatic changes. To address these questions, late-stage larvae of Synodus foetens, Synodus intermedius, Synodus poeyi, Saurida suspicio and Saurida brasiliensis were collected in replicate light traps in three different reef habitats (back-reef, lagoon and exposed) in the San Blas Archipelago, Panama, over 18 consecutive lunar months. Although replenishment of lizardfish occurred year-round, the temporal and spatial supply patterns were species-specific: S. foetens, S. intermedius and S. poeyi were most abundant during the dry season while S. suspicio and S. brasiliensis were most prevalent during the wet season. When seasons were analysed separately, water temperature explained 39 and 26% of the variance in light trap catches of S. foetens and S. intermedius, respectively, in the dry season while wind-induced turbulence accounted for 25% of the variability in S. suspicio and S. brasiliensis catches during the wet season. These findings stress the importance of analysing larval supply in conjunction with environmental data at a high taxonomic resolution to better understand the mechanisms that drive replenishment in reef systems at low latitudes