Raúl González-Domínguez

Combination of metabolomic and phospholipid-profiling approaches for the study of Alzheimer's disease☆

UNLABELLED Alzheimers disease is closely related to abnormal metabolism of phospholipids from neural membranes, so that the study of their dyshomeostasis could be of great interest for the discovery of potential biomarkers for diagnosis and disease monitoring. In this work, it has been developed a metabolomic multi-platform for the characterization of phospholipid alterations occurring in serum from Alzheimers disease patients. For this purpose, we performed a metabolomic screening by direct infusion mass spectrometry and profiling analysis by reversed phase ultra-high performance liquid chromatography with complementary detection by molecular and atomic mass spectrometry, which allowed combining the high-throughput capability of shotgun metabolomics and the targeted character of profiling approaches. Thus significant changes were detected in the levels of several molecular species of phosphatidylcholines, phosphatidylethanolamines, plasmenylcholines, plasmenylethanolamines and different classes of lysophospholipids, which provided a global vision of the possible factors triggering membrane breakdown. In this sense, alterations of phospholipids metabolism appears to have a multifactorial origin involving overactivation of phospholipases, increased anabolism of lysophospholipids, peroxisomal dysfunction, imbalances in the levels of saturated/unsaturated fatty acids contained in the structure of phospholipids and oxidative stress. BIOLOGICAL SIGNIFICANCE This work represents the first comprehensive characterization of serum phospholipids alterations in relation to Alzheimers disease, by combining shotgun metabolomics and phospholipids profiling through different analytical approaches.This article is part of a Special Issue entitled: Environmental and structural proteomics.

Metabolomic study of lipids in serum for biomarker discovery in Alzheimer's disease using direct infusion mass spectrometry

In this study, we demonstrated the potential of direct infusion mass spectrometry for the lipidomic characterization of Alzheimers disease. Serum samples were extracted for lipids recovery, and directly analyzed using an electrospray source. Metabolomic fingerprints were subjected to multivariate analysis in order to discriminate between groups of patients and healthy controls, and then some key-compounds were identified as possible markers of Alzheimers disease. Major differences were found in lipids, although some low molecular weight metabolites also showed significant changes. Thus, important metabolic pathways involved in neurodegeneration could be studied on the basis of these perturbations, such as membrane breakdown (phospholipids and diacylglycerols), oxidative stress (prostaglandins, imidazole and histidine), alterations in neurotransmission systems (oleamide and putrescine) and hyperammonaemia (guanidine and arginine). Moreover, it is noteworthy that some of these potential biomarkers have not been previously described for Alzheimers disease.

Metabolomic profiling of serum in the progression of Alzheimer's disease by capillary electrophoresis–mass spectrometry

There is high interest in the discovery of early diagnostic biomarkers of Alzheimers disease, for which metabolomics exhibits a great potential. In this work, a metabolomic approach based on ultrafiltration and analysis by CE‐MS has been used to obtain representative fingerprints of polar metabolites from serum samples in order to distinguish between patients with Alzheimers disease, mild cognitive impairment, and healthy controls. By the use of partial least squares discriminant analysis it was possible to classify patients according to the disease stage and then identify potential markers. Significant increase was observed with progression of disease in levels of choline, creatinine, asymmetric dimethyl‐arginine, homocysteine‐cysteine disulfide, phenylalanyl‐phenylalanine, and different medium chain acylcarnitines. On the other hand, asparagine, methionine, histidine, carnitine, acetyl‐spermidine, and C5‐carnitine were reduced in these serum samples. In this way, multiple essential pathways were found implicated in the underlying pathology, such as oxidative stress or defects in energy metabolism. However, the most interesting results are related to the association of several vascular risk factors with Alzheimers disease.

Homeostasis of metals in the progression of Alzheimer's disease.

In order to study the involvement of metals in the progression of Alzheimer’s disease, serum samples from patients with Alzheimer and mild cognitive impairment were investigated. For this purpose, metal content was analyzed after size-fractionation of species and then, inter-element and inter-fraction ratios were computed. In this way, the analysis allowed discovering changes that could be used as markers of disease, but also provided a new insight into the interactions in the homeostasis of elements in neurodegeneration and its progression. Aluminum and labile forms of iron and copper were increased in demented patients, while manganese, zinc and selenium were reduced. Interestingly, levels of different elements, principally iron, aluminum and manganese, were closely inter-related, which could evidence a complex interdependency between the homeostasis of the different metals in this disorder. On the other hand, imbalances in metabolism of copper, zinc and selenium could be associated to abnormal redox status. Therefore, this study may contribute to our understanding of the pathological mechanisms related to metals in Alzheimer’s disease.

Metabolite profiling for the identification of altered metabolic pathways in Alzheimer's disease

Gas chromatography coupled to mass spectrometry is the most frequent tool for metabolomic profiling of low molecular weight metabolites. Its suitability in health survey is beyond doubt, given that primary metabolites involved in central pathways of metabolism are usually altered in diseases. The objective of this work is to investigate metabolic differences in serum between Alzheimers disease patients and healthy controls in order to elucidate pathological mechanisms underlying to disease. Alterations in levels of 23 metabolites were detected, including increased lactic acid, α-ketoglutarate, isocitric acid, glucose, oleic acid, adenosine and cholesterol, as well as decreased urea, valine, aspartic acid, pyroglutamate, glutamine, phenylalanine, asparagine, ornithine, pipecolic acid, histidine, tyrosine, palmitic and uric acid, tryptophan, stearic acid and cystine. Metabolic pathway analysis revealed the involvement of multiple affected pathways, such as energy deficiencies, oxidative stress, hyperammonemia, and others. Moreover, it is noteworthy that some of these compounds have not been previously described in AD research, such as α-ketoglutarate, isocitrate pipecolic acid, pyroglutamate and adenosine, confirming the potential of this metabolomic approach in the search of novel potential markers for early detection of Alzheimers disease.

Region-specific metabolic alterations in the brain of the APP/PS1 transgenic mice of Alzheimer's disease

Alzheimers disease (AD) is the most common neurodegenerative disorder worldwide, but its etiology is still not completely understood. The identification of underlying pathological mechanisms is becoming increasingly important for the discovery of biomarkers and therapies, for which metabolomics presents a great potential. In this work, we studied metabolic alterations in different brain regions of the APP/PS1 mice by using a high-throughput metabolomic approach based on the combination of gas chromatography-mass spectrometry and ultra-high performance liquid chromatography-mass spectrometry. Multivariate statistics showed that metabolomic perturbations are widespread, affecting mainly the hippocampus and the cortex, but are also present in regions not primarily associated with AD such as the striatum, cerebellum and olfactory bulbs. Multiple metabolic pathways could be linked to the development of AD-type disorders in this mouse model, including abnormal purine metabolism, bioenergetic failures, dyshomeostasis of amino acids and disturbances in membrane lipids, among others. Interestingly, region-specific alterations were observed for some of the potential markers identified, associated with abnormal fatty acid composition of phospholipids and sphingomyelins, or differential regulation of neurotransmitter amino acids (e.g. glutamate, glycine, serine, N-acetyl-aspartate), not previously described to our knowledge. Therefore, these findings could provide a new insight into brain pathology in Alzheimers disease.

Application of a novel metabolomic approach based on atmospheric pressure photoionization mass spectrometry using flow injection analysis for the study of Alzheimer׳s disease

The use of atmospheric pressure photoionization is not widespread in metabolomics, despite its considerable potential for the simultaneous analysis of compounds with diverse polarities. This work considers the development of a novel analytical approach based on flow injection analysis and atmospheric pressure photoionization mass spectrometry for rapid metabolic screening of serum samples. Several experimental parameters were optimized, such as type of dopant, flow injection solvent, and their flows, given that a careful selection of these variables is mandatory for a comprehensive analysis of metabolites. Toluene and methanol were the most suitable dopant and flow injection solvent, respectively. Moreover, analysis in negative mode required higher solvent and dopant flows (100 µl min(-1) and 40 µl min(-1), respectively) compared to positive mode (50 µl min(-1) and 20 µl min(-1)). Then, the optimized approach was used to elucidate metabolic alterations associated with Alzheimers disease. Thereby, results confirm the increase of diacylglycerols, ceramides, ceramide-1-phosphate and free fatty acids, indicating membrane destabilization processes, and reduction of fatty acid amides and several neurotransmitters related to impairments in neuronal transmission, among others. Therefore, it could be concluded that this metabolomic tool presents a great potential for analysis of biological samples, considering its high-throughput screening capability, fast analysis and comprehensive metabolite coverage.

Metabolomic screening of regional brain alterations in the APP/PS1 transgenic model of Alzheimer's disease by direct infusion mass spectrometry

The identification of pathological mechanisms underlying to Alzheimers disease is of great importance for the discovery of potential markers for diagnosis and disease monitoring. In this study, we investigated regional metabolic alterations in brain from the APP/PS1 mice, a transgenic model that reproduces well some of the neuropathological and cognitive deficits observed in human Alzheimers disease. For this purpose, hippocampus, cortex, cerebellum and olfactory bulbs were analyzed using a high-throughput metabolomic approach based on direct infusion mass spectrometry. Metabolic fingerprints showed significant differences between transgenic and wild-type mice in all brain tissues, being hippocampus and cortex the most affected regions. Alterations in numerous metabolites were detected including phospholipids, fatty acids, purine and pyrimidine metabolites, acylcarnitines, sterols and amino acids, among others. Furthermore, metabolic pathway analysis revealed important alterations in homeostasis of lipids, energy management, and metabolism of amino acids and nucleotides. Therefore, these findings demonstrate the potential of metabolomic screening and the use of transgenic models for understanding pathogenesis of Alzheimers disease.

Using direct infusion mass spectrometry for serum metabolomics in Alzheimer's disease.

AbstractCurrently, there is no cure for Alzheimer’s disease and early diagnosis is very difficult, since no biomarkers have been established with the necessary reliability and specificity. For the discovery of new biomarkers, the application of omics is emerging, especially metabolomics based on the use of mass spectrometry. In this work, an analytical approach based on direct infusion electrospray mass spectrometry was applied for the first time to blood serum samples in order to elucidate discriminant metabolites. Complementary methodologies of extraction and mass spectrometry analysis were employed for comprehensive metabolic fingerprinting. Finally, the application of multivariate statistical tools allowed us to discriminate Alzheimer patients and healthy controls, and identify some compounds as potential markers of disease. This approach provided a global vision of disease, given that some important metabolic pathways could be studied, such as membrane destabilization processes, oxidative stress, hypometabolism, or neurotransmission alterations. Most remarkable results are the high levels of phospholipids containing saturated fatty acids, respectively, polyunsaturated ones and the high concentration of whole free fatty acids in Alzheimer’s serum samples. Thus, these results represent an interesting approximation to understand the pathogenesis of disease and the identification of potential biomarkers. Graphical Abstractᅟ

Development of a metabolomic approach based on urine samples and direct infusion mass spectrometry.

The analysis of urine by direct infusion mass spectrometry suffers from ion suppression due to its high salt content and inter-sample variability caused by the differences in urine volume between persons. Thus, urine metabolomics requires a careful selection of the sample preparation procedure and a normalization strategy to deal with these problems. Several approaches were tested for metabolomic analysis of urine samples by direct infusion electrospray mass spectrometry (DI-ESI-MS), including solid phase extraction, liquid-liquid extraction, and sample dilution. In addition, normalization of results based on conductivity values and statistical treatment was performed to minimize sample variability. Both urine dilution and solid phase extraction with mixed mode sorbent considerably reduced the salt content in urine, providing comprehensive metabolomic fingerprints. Moreover, statistical data normalization enabled the correction of inter-sample physiological variability, improving the quality of results obtained. Therefore, high-throughput DI-ESI-MS fingerprinting of urine samples can be achieved with simple pretreatment procedures allowing the use of this noninvasive sampling in metabolomics. Finally, the optimized approach was tested in a pilot metabolomic investigation of urine samples from transgenic mice models of Alzheimers disease (APP/PS1) in order to illustrate the potential of the methodology.