bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2022–02–06
sixteen papers selected by
Giovanny Rodríguez Blanco, University of Edinburgh
  1. Acyl-CoA Identification in Mouse Liver Samples Using the In Silico CoA-Blast Tandem Mass Spectral Library.
  2. Light contamination in stable isotope-labelled internal peptide standards is frequent and a potential source of false discovery and quantitation error in proteomics.
  3. A practical guide to interpreting and generating bottom-up proteomics data visualizations.
  4. Dysregulated lipid metabolism in colorectal cancer.
  5. Multiplexed Isobaric Quantitative Cross-Linking Reveals Drug-Induced Interactome Changes in Breast Cancer Cells.
  6. Methods for quantification of glycopeptides by liquid separation and mass spectrometry.
  7. Data-Independent Acquisition Approach to Proteome: A Case Study and a Spectral Library for Mass Spectrometry-Based Investigation of Mycobacterium tuberculosis.
  8. A knowledge graph to interpret clinical proteomics data.
  9. Proteomics Analysis of the Estrogen Effects in the Rat Uterus Using Gel-LC and Tandem Mass Spectrometry Approaches.
  10. Emerging Roles of the Tumor Suppressor p53 in Metabolism.
  11. Disrupted Liver Oxidative Metabolism in Glycine N-Methyltransferase-Deficient Mice is Mitigated by Dietary Methionine Restriction.
  12. Aberrant lipid metabolism reprogramming and immune microenvironment for gastric cancer: a literature review.
  13. Bioenergetic Metabolism In Osteoblast Differentiation.
  14. A LC-MS/MS method to simultaneously profile 14 free monosaccharides in biofluids.
  15. Proline synthesis through PYCR1 is required to support cancer cell proliferation and survival in oxygen-limiting conditions.
  16. Investigating the importance of acylcarnitines in Alzheimer's disease.
  1. Anal Chem. 2022 Feb 04.
    Acyl-CoA Identification in Mouse Liver Samples Using the In Silico CoA-Blast Tandem Mass Spectral Library.
    Uri Keshet, Tobias Kind, Xinchen Lu, Sarita Devi, Oliver Fiehn.
      Acyl-coenzyme A derivatives (acyl-CoAs) are core molecules in the fatty acid and energy metabolism across all species. However, in vivo, many other carboxylic acids can form xenobiotic acyl-CoA esters, including drugs. More than 2467 acyl-CoAs are known from the published literature. In addition, more than 300 acyl-CoAs are covered in pathway databases, but as of October 2020, only 53 experimental acyl-CoA tandem mass spectra are present in NIST20 and MoNA libraries to enable annotation of the mass spectra in untargeted metabolomics studies. The experimental spectra originated from low-resolution ion trap and triple quadrupole mass spectrometers as well as high-resolution quadrupole-time of flight and orbital ion trap instruments at various collision energies. We used MassFrontier software and the literature to annotate fragment ions to generate fragmentation rules and intensities for the different instruments and collision energies. These rules were then applied to 1562 unique species based on [M+H]+ and [M-H]- precursor ions to generate two mass spectra per instrument platform and collision energy, amassing an in silico library of 10,934 accurate mass MS/MS spectra that are freely available at github.com/urikeshet/CoA-Blast. The spectra can be imported into a commercial or freely available mass spectral search tool. We used the libraries to annotate 23 acyl-CoA esters in mouse liver, including 8 novel species.
    DOI:  https://doi.org/10.1021/acs.analchem.1c03272
  2. Anal Bioanal Chem. 2022 Feb 04.
    Light contamination in stable isotope-labelled internal peptide standards is frequent and a potential source of false discovery and quantitation error in proteomics.
    Mogjiborahman Salek, Jonas D Förster, Wolf-Dieter Lehmann, Angelika B Riemer.
      In mass spectrometry-based proteomics, heavy internal standards are used to validate target peptide detections and to calibrate peptide quantitation. Here, we report light contamination present in heavy labelled synthetic peptides of high isotopic enrichment. Application of such peptides as assay-internal standards potentially compromises the detection and quantitation especially of low abundant cellular peptides. Therefore, it is important to adopt guidelines to prevent false-positive identifications of endogenous light peptides as well as errors in their quantitation from biological samples.
    Keywords:  Immunopeptidomics; Internal standards; Mass spectrometry; Proteomics; Stable isotope-labelled (SIL) peptides
    DOI:  https://doi.org/10.1007/s00216-022-03931-w
  3. Proteomics. 2022 Feb 02. e2100103
    A practical guide to interpreting and generating bottom-up proteomics data visualizations.
    Julia Patricia Schessner, Eugenia Voytik, Isabell Bludau.
      Mass-spectrometry based bottom-up proteomics is the main method to analyze proteomes comprehensively and the rapid evolution of instrumentation and data analysis has made the technology widely available. Data visualization is an integral part of the analysis process and it is crucial for the communication of results. This is a major challenge due to the immense complexity of MS data. In this review, we provide an overview of commonly used visualizations, starting with raw data of traditional and novel MS technologies, then basic peptide and protein level analyses, and finally visualization of highly complex datasets and networks. We specifically provide guidance on how to critically interpret and discuss the multitude of different proteomics data visualizations. Furthermore, we highlight Python-based libraries and other open science tools that can be applied for independent and transparent generation of customized visualizations. To further encourage programmatic data visualization, we provide the Python code used to generate all data Figures in this review on GitHub (https://github.com/MannLabs/ProteomicsVisualization). This article is protected by copyright. All rights reserved.
    Keywords:  bottom-up proteomics; data visualization; open science; science communication
    DOI:  https://doi.org/10.1002/pmic.202100103
  4. Curr Opin Gastroenterol. 2022 Mar 01. 38(2): 162-167
    Dysregulated lipid metabolism in colorectal cancer.
    Olivia Coleman, Miriam Ecker, Dirk Haller.
       PURPOSE OF REVIEW: Lipid metabolism presents a targetable metabolic vulnerability in colorectal cancer (CRC). Lipid signatures and cancer-cell lipid requirements may serve as noninvasive diagnostic and prognostic biomarkers and as a therapeutic target, respectively.
    RECENT FINDINGS: A growing body of new studies highlight the complexity of lipid metabolism in CRC. Cancer cells are able to utilize an alternative fatty acid desaturation pathway, underlining the metabolic plasticity of tumors. CRC tissue shows a robust triglyceride-species signature with prognostic value in CRC patients. Lipidomic analyses in germfree and colonized mice identify a unique lipid signature and suggest that bacteria inhibit metabolism of polyunsaturated fatty acids by blocking desaturase and elongase activities. Cellular stress responses, particularly the well characterized unfolded protein response, are involved in regulating lipid synthesis and homeostasis, and contribute to adaptation of the lipid environment. Together, lipid metabolism, the intestinal microbiota and cellular stress responses unarguably play crucial roles in CRC.
    SUMMARY: A number of recent advances in our understanding of dysregulated lipid metabolism in CRC underline the importance of this research field. An improved knowledge of the complex interplay between lipid metabolism, cellular stress and the intestinal microbiota in the context of CRC may lead to novel therapeutic strategies.
    DOI:  https://doi.org/10.1097/MOG.0000000000000811
  5. Anal Chem. 2022 Feb 02.
    Multiplexed Isobaric Quantitative Cross-Linking Reveals Drug-Induced Interactome Changes in Breast Cancer Cells.
    Helisa H Wippel, Juan D Chavez, Andrew D Keller, James E Bruce.
      The study of protein structures and interactions is critical to understand their function. Chemical cross-linking of proteins with mass spectrometry (XL-MS) is a rapidly developing structural biology technique able to provide valuable insight into protein conformations and interactions, even as they exist within their native cellular environment. Quantitative analysis of cross-links can reveal protein conformational and interaction changes that occur as a result of altered biological states, environmental conditions, or pharmacological perturbations. Our laboratory recently developed an isobaric quantitative protein interaction reporter (iqPIR) cross-linking strategy for comparative interactome studies. This strategy relies on isotope encoded chemical cross-linkers that have the same molecular mass yet produce unique and specific isotope signatures upon fragmentation in the mass spectrometer which can be used for quantitative analysis of cross-linked peptides. The initial set of iqPIR molecules allowed for binary comparisons. Here, we describe the in vivo application of an extended set of six iqPIR reagents (6-plex iqPIR), allowing multiplexed quantitative interactome analysis of up to six biological samples in a single LC-MS acquisition. Multiplexed iqPIR is demonstrated on MCF-7 breast cancer cells treated with five different Hsp90 inhibitors revealing large scale protein conformational and interaction changes specific to the molecular class of the inhibitors.
    DOI:  https://doi.org/10.1021/acs.analchem.1c02208
  6. Mass Spectrom Rev. 2022 Jan 31. e21771
    Methods for quantification of glycopeptides by liquid separation and mass spectrometry.
    Haidi Yin, Jianhui Zhu.
      Recent advances in analytical techniques provide the opportunity to quantify even low-abundance glycopeptides derived from complex biological mixtures, allowing for the identification of glycosylation differences between healthy samples and those derived from disease states. Herein, we discuss the sample preparation procedures and the mass spectrometry (MS) strategies that have facilitated glycopeptide quantification, as well as the standards used for glycopeptide quantification. For sample preparation, various glycopeptide enrichment methods are summarized including the columns used for glycopeptide separation in liquid chromatography separation. For MS analysis strategies, MS1 level-based quantification and MS2 level-based quantification are described, either with or without labeling, where we have covered isotope labeling, TMT/iTRAQ labeling, data dependent acquisition, data independent acquisition, multiple reaction monitoring, and parallel reaction monitoring. The strengths and weaknesses of these methods are compared, particularly those associated with the figures of merit that are important for clinical biomarker studies and the pathological and functional studies of glycoproteins in various diseases. Possible future developments for glycopeptide quantification are discussed.
    DOI:  https://doi.org/10.1002/mas.21771
  7. OMICS. 2022 Jan 28.
    Data-Independent Acquisition Approach to Proteome: A Case Study and a Spectral Library for Mass Spectrometry-Based Investigation of Mycobacterium tuberculosis.
    Kriti Awasthi, Chinmaya Narayana Kootimole, Anjana Aravind, Thottethodi Subrahmanya Keshava Prasad.
      Currently, mass spectrometry-based data-dependent acquisition protocols require several micrograms to milligram amounts of proteins to start with, and needs fractionation and enrichment or depletion protocols to identify low abundant proteins and their modifications. However, a data-independent acquisition (DIA) approach can help us to identify a large number of proteins irrespective of their abundance, from even a very low amount of protein. In the DIA protocol, mass spectrometry data are matched against a previously established tandem mass spectrometry (MS/MS) spectra for each peptide. Therefore, establishing a spectral library is a prerequisite for successful DIA protocol. However, the DIA protocol becomes extremely important to investigate biological systems, where there is a difficulty in gathering reasonable amounts of proteins. In this context, DIA can become a valuable tool to investigate proteome dynamics of slow growing pathogen such as Mycobacterium tuberculosis that causes tuberculosis. We report here a case study of the DIA approach that is ideal for M. tuberculosis, which cannot be scaled up easily as it requires specific BSL3 laboratory facilities to be grown. We generated a spectral library for M. tuberculosis proteome using six publicly available proteomic data sets. The in-house M. tuberculosis proteome spectral library contains MS/MS spectra for peptides corresponding to 88% of proteins when compared with the M. tuberculosis H37Rv proteome. We believe that the public availability of the M. tuberculosis spectral library is an important step forward to facilitate the research community to adopt DIA approaches, for example, to investigate M. tuberculosis proteome with greater depth and efficiency.
    Keywords:  data-dependent acquisition; global health; omics; proteomics; spectral library; tuberculosis
    DOI:  https://doi.org/10.1089/omi.2021.0187
  8. Nat Biotechnol. 2022 Jan 31.
    A knowledge graph to interpret clinical proteomics data.
    Alberto Santos, Ana R Colaço, Annelaura B Nielsen, Lili Niu, Maximilian Strauss, Philipp E Geyer, Fabian Coscia, Nicolai J Wewer Albrechtsen, Filip Mundt, Lars Juhl Jensen, Matthias Mann.
      Implementing precision medicine hinges on the integration of omics data, such as proteomics, into the clinical decision-making process, but the quantity and diversity of biomedical data, and the spread of clinically relevant knowledge across multiple biomedical databases and publications, pose a challenge to data integration. Here we present the Clinical Knowledge Graph (CKG), an open-source platform currently comprising close to 20 million nodes and 220 million relationships that represent relevant experimental data, public databases and literature. The graph structure provides a flexible data model that is easily extendable to new nodes and relationships as new databases become available. The CKG incorporates statistical and machine learning algorithms that accelerate the analysis and interpretation of typical proteomics workflows. Using a set of proof-of-concept biomarker studies, we show how the CKG might augment and enrich proteomics data and help inform clinical decision-making.
    DOI:  https://doi.org/10.1038/s41587-021-01145-6
  9. Methods Mol Biol. 2022 ;2418 289-311
    Proteomics Analysis of the Estrogen Effects in the Rat Uterus Using Gel-LC and Tandem Mass Spectrometry Approaches.
    Maria D Paez, Eduardo A Callegari.
      Proteomics-based bottoms-up, at a big scale applied to the protein identification and relative quantification present in complex mixtures (cell lysates, tissues, biological fluids, secretome, etc.) is a useful strategy to identify proteins and analyze their changes. Samples processed through a gel-free approach provide a simple method for protein separation and profile comparison of different conditions, such as using fewer steps in the protocol, reducing excessive sample handling, and covering an extended range of molecular weights and isoelectric points. However, it presents a great limitation related to the management of large dynamic ranges of proteins. There are numerous protocols that allow handling the problem or limitations generated by a high dynamic range of the proteins present in the sample. The Gel-LC technique is a complementary alternative of the gel-free approach available to solve the issue of protein samples with a high dynamic range. The different steps of the protocol involve sample processing through Gel-LC (1D-SDS-PAGE) prior to digestion, 1D-nanoUHPLC coupled to high-resolution/mass accuracy tandem mass spectrometry analysis (1D-nanoUHPLC-HR/MA-MS /MS analysis) and afterward, the protein identification and relative quantification analysis using bioinformatics tools for the data conversion, organization, and interpretation.
    Keywords:  Bioinformatics; Estrogen; Gel-LC; Liquid chromatography; Mass spectrometry; Peptides; Proteins; Proteomics; Rat; Uterus
    DOI:  https://doi.org/10.1007/978-1-0716-1920-9_17
  10. Front Cell Dev Biol. 2021 ;9 762742
    Emerging Roles of the Tumor Suppressor p53 in Metabolism.
    Lili Yu, Meng Wu, Gaoyang Zhu, Yang Xu.
      Metabolism plays critical roles in maintaining the homeostasis of cells. Metabolic abnormalities are often considered as one of the main driving forces for cancer progression, providing energy and substrates of biosynthesis to support neoplastic proliferation effectively. The tumor suppressor p53 is well known for its roles in inducing cell cycle arrest, apoptosis, senescence and ferroptosis. Recently, emerging evidence has shown that p53 is also actively involved in the reprogramming of cellular metabolism. In this review, we focus on recent advances in our understanding of the interplay between p53 and metabolism of glucose, fatty acid as well as amino acid, and discuss how the deregulation of p53 in these processes could lead to cancer.
    Keywords:  amino acid metabolism; ferroptosis; glucose metabolism; iron metabolism; lipid metabolism; p53
    DOI:  https://doi.org/10.3389/fcell.2021.762742
  11. Mol Metab. 2022 Feb 01. pii: S2212-8778(22)00021-7. [Epub ahead of print] 101452
    Disrupted Liver Oxidative Metabolism in Glycine N-Methyltransferase-Deficient Mice is Mitigated by Dietary Methionine Restriction.
    Ferrol I Rome, Curtis C Hughey.
       OBJECTIVE: One-carbon metabolism is routinely dysregulated in nonalcoholic fatty liver disease. This includes decreased glycine N-methyltransferase (GNMT), a critical regulator of s-adenosylmethionine (SAM). Deletion of GNMT in mice increases SAM and promotes liver steatosis. Lower liver oxidative metabolism as indicated by a decline in gluconeogenesis, citric acid cycle flux, and oxidative phosphorylation contributes to liver steatosis in GNMT-null mice, however, the extent to which this phenotype is mediated by higher SAM remains unclear. Here, we determined the SAM-dependent impairment in liver oxidative metabolism by loss of GNMT.
    METHODS: GNMT knockout (KO) mice were fed a methionine-restricted diet to prevent increased SAM. 2H/13C metabolic flux analysis was performed in conscious, unrestrained mice to quantify liver nutrient fluxes. Metabolomics and high-resolution respirometry was used to quantify liver nutrient pool sizes and mitochondrial oxidative phosphorylation, respectively. Folic acid-supplemented and serine/glycine-deficient diets were used independently to further define the metabolic implications of perturbed one-carbon donor availability.
    RESULTS: Dietary methionine restriction prevented a 75-fold increase in SAM and 53% rise in triacylglycerides in livers of KO mice. Dietary methionine restriction increased gluconeogenesis independent of genotype and restored cytochrome c oxidase respiratory function in KO mice. Citric acid cycle fluxes remained lower in KO mice irrespective of diet. Restricting dietary methionine abrogated markers of increased lipogenesis and folate cycle dysfunction in KO mice.
    CONCLUSION: The impaired liver oxidative metabolism following loss of GNMT is both dependent and independent of greater SAM availability. Lower in vivo citric acid cycle flux is independent of increased SAM. In contrast, gluconeogenesis and oxidative phosphorylation are negatively regulated by excess SAM. Lipid accumulation in livers of mice lacking GNMT is also linked to the higher SAM.
    Keywords:  citric acid cycle; gluconeogenesis; lipogenesis; nonalcoholic fatty liver disease; one-carbon metabolism; oxidative phosphorylation
    DOI:  https://doi.org/10.1016/j.molmet.2022.101452
  12. Transl Cancer Res. 2021 Aug;10(8): 3829-3842
    Aberrant lipid metabolism reprogramming and immune microenvironment for gastric cancer: a literature review.
    Meng-Ying Cui, Xing Yi, Dan-Xia Zhu, Jun Wu.
       Objective: We summarize the aberrant lipid metabolism disorders associated with enzyme activity and expression changes and related immune microenvironment for gastric cancer.
    Background: Gastric cancer is a malignant tumor of the primary digestive system with high incidence, poor prognosis characterized by extensive metastasis and poor effect with radiotherapy and chemotherapy. One of the most important metabolic characteristics of cancer cells is lipid metabolism reprogramming to adapt to the tumor micro-environment.
    Methods: The focus of research in recent years has also been on lipid metabolism disorders, particularly aberrant metabolism of fatty acids (FAs) in gastric cancer cells, as well as an upregulation of the expression and activity of key enzymes in lipid metabolism. These changes remind us of the occurrence and development of gastric cancer. These metabolic changes are not unique to cancer cells. Changes in metabolic procedures also determine the function and viability of immune cells. In the immune microenvironment of gastric cancer, the metabolic competition and interaction between cancer cells and immune cells are not very clear, while a deeper understanding of the topic is critical to targeting the differential metabolic requirements of them that comprise an immune response to cancer offers an opportunity to selectively regulate immune cell function.
    Conclusions: Recent research suggests that targeting metabolism is an emerging and potentially promising treatment strategy for gastric cancer patients. We need to explore it further.
    Keywords:  Lipid metabolism related enzymes; gastric cancer; targeted metabolism treatment; tumor immunosuppression microenvironment
    DOI:  https://doi.org/10.21037/tcr-21-655
  13. Curr Osteoporos Rep. 2022 Feb 03.
    Bioenergetic Metabolism In Osteoblast Differentiation.
    Leyao Shen, Guoli Hu, Courtney M Karner.
       PURPOSE OF REVIEW: Osteoblasts are responsible for bone matrix production during bone development and homeostasis. Much is known about the transcriptional regulation and signaling pathways governing osteoblast differentiation. However, less is known about how osteoblasts obtain or utilize nutrients to fulfill the energetic demands associated with osteoblast differentiation and bone matrix synthesis. The goal of this review is to highlight and discuss what is known about the role and regulation of bioenergetic metabolism in osteoblasts with a focus on more recent studies.
    RECENT FINDINGS: Bioenergetic metabolism has emerged as an important regulatory node in osteoblasts. Recent studies have begun to identify the major nutrients and bioenergetic pathways favored by osteoblasts as well as their regulation during differentiation. Here, we highlight how osteoblasts obtain and metabolize glucose, amino acids, and fatty acids to provide energy and other metabolic intermediates. In addition, we highlight the signals that regulate nutrient uptake and metabolism and focus on how energetic metabolism promotes osteoblast differentiation. Bioenergetic metabolism provides energy and other metabolites that are critical for osteoblast differentiation and activity. This knowledge contributes to a more comprehensive understanding of osteoblast biology and may inform novel strategies to modulate osteoblast differentiation and bone anabolism in patients with bone disorders.
    Keywords:  Amino acids; Bioenergetics; Bone; Glycolysis; Osteoblast; β-oxidation
    DOI:  https://doi.org/10.1007/s11914-022-00721-2
  14. J Chromatogr B Analyt Technol Biomed Life Sci. 2022 Jan 12. pii: S1570-0232(21)00567-5. [Epub ahead of print]1192 123086
    A LC-MS/MS method to simultaneously profile 14 free monosaccharides in biofluids.
    Hao Wang, Xi Zhang, Yingfei Peng, Baishen Pan, Beili Wang, David Haixiang Peng, Wei Guo.
      Monosaccharides are important players in cell metabolism and potential biomarkers. An effective tool to quantify monosaccharides is required in basic research and healthcare. In this study, we developed a liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay that could simultaneously quantify 14 free monosaccharides and evaluated its performance according to clinical guidance. The LC-MS/MS step separated and quantified 14 monosaccharides with 6 min. The coefficient of variation at the lower limit of quantification was less than 20% for each analyte. The R square values from linear regression analyses were all greater than 0.995. The validated assay was employed to profile free monosaccharides in conditioned media from cell culture and patient sera from glucose tolerance test. Both LO2 cells and HEK293 cells consumed D-glucosamine, D-glucose and produced D-glucuronic acid, N-acetyl-D-glucosamine. Additionally, LO2 cells produced D-mannose and L-fucose, whereas HEK293 cells consumed D-mannose. In patient sera from glucose tolerance test, the level of D-glucose increased significantly after glucose intake, but the levels of other monosaccharides didn't. In conclusion, the LC-MS/MS assay we developed for 14-monosaccharide profiling met clinical requirements. The monosaccharide profiling results showed the distinct monosaccharide metabolism between liver and kidney cells, and the ignorable diet effect on 6 serum monosaccharides.
    Keywords:  Biofluid; Biomarker; Free monosaccharide; LC-MS/MS; Profiling
    DOI:  https://doi.org/10.1016/j.jchromb.2021.123086
  15. Cell Rep. 2022 Feb 01. pii: S2211-1247(22)00031-6. [Epub ahead of print]38(5): 110320
    Proline synthesis through PYCR1 is required to support cancer cell proliferation and survival in oxygen-limiting conditions.
    Rebecca L Westbrook, Esther Bridges, Jennie Roberts, Cristina Escribano-Gonzalez, Katherine L Eales, Lisa A Vettore, Paul D Walker, Elias Vera-Siguenza, Himani Rana, Federica Cuozzo, Kattri-Liis Eskla, Hans Vellama, Abeer Shaaban, Colin Nixon, Hendrik Luuk, Gareth G Lavery, David J Hodson, Adrian L Harris, Daniel A Tennant.
      The demands of cancer cell proliferation alongside an inadequate angiogenic response lead to insufficient oxygen availability in the tumor microenvironment. Within the mitochondria, oxygen is the major electron acceptor for NADH, with the result that the reducing potential produced through tricarboxylic acid (TCA) cycle activity and mitochondrial respiration are functionally linked. As the oxidizing activity of the TCA cycle is required for efficient synthesis of anabolic precursors, tumoral hypoxia could lead to a cessation of proliferation without another means of correcting the redox imbalance. We show that in hypoxic conditions, mitochondrial pyrroline 5-carboxylate reductase 1 (PYCR1) activity is increased, oxidizing NADH with the synthesis of proline as a by-product. We further show that PYCR1 activity is required for the successful maintenance of hypoxic regions by permitting continued TCA cycle activity, and that its loss leads to significantly increased hypoxia in vivo and in 3D culture, resulting in widespread cell death.
    Keywords:  NADH; PYCR1; cancer; hypoxia; mitochondria; proline; redox
    DOI:  https://doi.org/10.1016/j.celrep.2022.110320
  16. Alzheimers Dement. 2021 Dec;17 Suppl 3 e056647
    Investigating the importance of acylcarnitines in Alzheimer's disease.
    Priyanka Baloni, Kwangsik Nho, Matthias Arnold, Gregory Louie, Alexandra Kueider-Paisley, Andrew J Saykin, Kim Ekroos, Cory Funk, Leroy Hood, Nathan D Price, Rebecca Baillie, Gabi Kastenmüller, Xianlin Han, Rima F Kaddurah-Daouk.
       BACKGROUND: L-carnitine is present in the mammalian cells as free carnitine (FC) and acylcarnitine and the adult human brain contains almost 10% of long chain acylcarnitine. Acylcarnitines are functionally involved in β-oxidation of fatty acids and are also known for their role in neuroprotection. Levels of plasma acylcarnitines are known to decreased on aging. It is important to understand the association of acylcarnitines with cognitive impairment in Alzheimer's disease (AD).
    METHOD: We integrated the transcriptome data from 1000 post-mortem brain samples from ROS/MAP, Mayo clinic and Mount Sinai Brain bank cohort with the brain region-specific metabolic networks. We calculated the metabolic fluxes for the reactions in the model and identified those that showed differential fluxes in AD samples. We filtered the reactions that are involved in acylcarnitine synthesis and transport namely carnitine transport, fatty acid oxidation, citric acid cycle, and glutathione metabolism.
    RESULT: We found differences in metabolic fluxes for reactions involved in the acetylcarnitine transport to mitochondria (ACRNtm), carnitine palmitoyl transferase 1 and 2 (CPT1 and CPT2) as well as acyl-CoA dehydrogenase short and medium chain (ACADS, ACADM) located in mitochondria in AD samples. Using gene-based association analysis in participants of the AD Neuroimaging Initiative (ADNI) phases 1, GO and 2, we identified genetic variants linked to CPT1, CPT2, ACADM and ACADS genes suggested from the metabolic flux analysis.
    CONCLUSION: Our findings suggest that acylcarnitine synthesis and transport is altered in AD. Altered metabolism of short and medium chain acylcarnitines can be used as metabolic features of AD.
    DOI:  https://doi.org/10.1002/alz.056647
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