{"id":5169,"date":"2025-03-02T20:15:38","date_gmt":"2025-03-02T20:15:38","guid":{"rendered":"https:\/\/www.ub.edu\/nutrimetabolomics\/blog\/"},"modified":"2025-03-02T20:15:40","modified_gmt":"2025-03-02T20:15:40","slug":"new-development-of-a-comprehensive-targeted-metabolomics-assay-to-analyze-metabolites-in-serum-and-plasma-samples","status":"publish","type":"post","link":"https:\/\/www.ub.edu\/nutrimetabolomics\/blog\/new-development-of-a-comprehensive-targeted-metabolomics-assay-to-analyze-metabolites-in-serum-and-plasma-samples\/","title":{"rendered":"New development of a comprehensive targeted metabolomics assay to analyze metabolites in serum and plasma samples."},"content":{"rendered":"<div\nclass=\"omt-container has-none-background-color omt-container__wrapper--none wp-block-omt-container\" id=\"block_9cfd88505e7706cb9756fb1642d6cd3f\">\n\t<div class=\"omt-container__wrapper omt-container__wrapper--normal omt-container__wrapper--offset-\">\n\t\t<div class=\"acf-innerblocks-container\">\n\n<h2 class=\"wp-block-heading\">New development of a comprehensive targeted metabolomics assay to analyze metabolites in serum and plasma samples.<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Metabolomics has achieved a groundbreaking advancement with the development of a new and comprehensive targeted metabolomics assay to analyze metabolites in serum and plasma samples.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This project, led in collaboration by Dr. David S. Wishart\u2019s group at the Metabolomics Innovation Centre (TMIC) at the University of Alberta, Canada, and Dr. Cristina Andres-Lacueva\u2019s group at the Nutritional and Food Biomarkers and Metabolomics Research Group at the University of Barcelona-CIBERFES, Spain, aims to address a key limitation of traditional targeted metabolomics, which typically covers fewer than 200 metabolites.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The limited metabolite coverage has restricted the impact of targeted metabolomics in clinical research and biomarker discovery. In response, this team has developed the MEGA assay, which quantifies more than 700 metabolites, significantly enhancing the analytical depth of metabolomics research and enabling a greater understanding of various biochemical pathways.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Technological Innovation Behind MEGA<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">The MEGA assay utilizes liquid chromatography coupled with tandem mass spectrometry (LC\u2013MS\/MS) in multiple reaction monitoring (MRM) mode, achieving both high precision and broad metabolite coverage. Isotopically labeled internal standards (ISTDs) were used along with isotopically labeled derivatization reagents to ensure accurate metabolite quantification.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Additionally, the assay employs a <strong>96-well plate format<\/strong>, enabling <strong>high-throughput sample processing<\/strong>. <strong>Sample preparation<\/strong> includes two derivatization steps: <strong>phenylisothiocyanate (PITC)<\/strong> for amino acids, biogenic amines, and lipids, and <strong>3-nitrophenylhydrazine (3-NPH)<\/strong> for organic acids. The analysis is performed using a <strong>UHPLC-QTRAP system<\/strong> with <strong>four methods<\/strong> and short run times:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Reverse-phase LC methods:<\/strong>\n<ul class=\"wp-block-list\">\n<li><strong>Panel A<\/strong> (amino acids, biogenic amines; <strong>9-minute run time<\/strong>)<\/li>\n\n\n\n<li><strong>Panel B<\/strong> (organic acids; <strong>12-minute run time<\/strong>)<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li><strong>Direct Flow Injection (DFI) methods:<\/strong>\n<ul class=\"wp-block-list\">\n<li><strong>DFI 1 and DFI 2<\/strong> (lipids; <strong>3-minute run time each<\/strong>)<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">Data quantification is carried out using a proprietary web-based tool called LC-Autofit, which allows for rapid analysis and report generation within hours.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This setup not only ensures high accuracy in metabolite quantification but also makes the process efficient and cost-effective for handling large sample volumes, which is essential for studies aiming to identify metabolic biomarkers across diverse patient groups..<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Broad Metabolite Coverage for Clinical Insights<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">With the ability to detect and quantify <strong>721 metabolites<\/strong> across <strong>20 chemical classes<\/strong>, including 64 amino acids and derivatives, 53 organic acids, 19 biogenic amines, 22 nucleobases and nucleosides, 4 catecholamines, 9 metabolites from the kynurenine-tryptophan pathway, 7 ketones and keto acids, 9 indole derivatives, 3 vitamins and derivatives, 4 sulfates, 1 dipeptide, 242 triglycerides, 75 phosphatidylcholines, 40 acylcarnitines, 22 cholesterol esters, 44 diglycerides, 36 ceramides, 19 hexosylceramides, 14 lysophosphatidylcholines, 14 sphingomyelins, 9 dihexosylceramides, 6 trihexosylceramides, 2 sugars, and 3 miscellaneous metabolites, the MEGA assay provides unprecedented coverage of clinically relevant metabolites that play essential roles in health and disease.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Researchers and clinicians can leverage this comprehensive metabolic profiling to <strong>identify novel biomarkers<\/strong> for conditions such as <strong>cardiovascular diseases, cognitive decline, and metabolic disorders<\/strong>, representing a <strong>transformative advancement<\/strong> in <strong>precision diagnostics and therapeutic monitoring<\/strong>.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"1024\" height=\"353\" src=\"https:\/\/www.ub.edu\/nutrimetabolomics\/wp-content\/uploads\/2025\/02\/Captura-de-pantalla-2025-02-02-a-les-20.05.33-1-1024x353.jpg\" alt=\"\" class=\"wp-image-4327\" srcset=\"https:\/\/www.ub.edu\/nutrimetabolomics\/wp-content\/uploads\/2025\/02\/Captura-de-pantalla-2025-02-02-a-les-20.05.33-1-1024x353.jpg 1024w, https:\/\/www.ub.edu\/nutrimetabolomics\/wp-content\/uploads\/2025\/02\/Captura-de-pantalla-2025-02-02-a-les-20.05.33-1-300x103.jpg 300w, https:\/\/www.ub.edu\/nutrimetabolomics\/wp-content\/uploads\/2025\/02\/Captura-de-pantalla-2025-02-02-a-les-20.05.33-1-768x264.jpg 768w, https:\/\/www.ub.edu\/nutrimetabolomics\/wp-content\/uploads\/2025\/02\/Captura-de-pantalla-2025-02-02-a-les-20.05.33-1-1536x529.jpg 1536w, https:\/\/www.ub.edu\/nutrimetabolomics\/wp-content\/uploads\/2025\/02\/Captura-de-pantalla-2025-02-02-a-les-20.05.33-1-480x165.jpg 480w, https:\/\/www.ub.edu\/nutrimetabolomics\/wp-content\/uploads\/2025\/02\/Captura-de-pantalla-2025-02-02-a-les-20.05.33-1.jpg 1876w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Rigorous Validation and Real-World Applications<\/strong><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>The assay has undergone rigorous validation through extensive calibration, precision, and accuracy testing, meeting high standards in metabolomics research.<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The detection limits were determined to range between 1.4 nM and 10 mM, with recovery rates between 80% and 120%, and quantitative precision below 20%. Its performance was confirmed through comparison with NMR spectroscopy using a known plasma standard, <strong>the NIST\u00ae SRM 1950\u00ae plasma standard<\/strong>, which showed strong correlation with deviations of less than 15%.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The assay\u2019s value was also demonstrated in a clinical study focused on <strong>mild cognitive impairment<\/strong>, where it helped measure metabolic changes in response to a Mediterranean diet intervention. Significant compounds with decreased concentrations, such as <strong>ceramides, glucosylceramides, triglycerides, and phosphatidylcholines<\/strong>, could indicate an improvement in cognitive decline, as their levels were observed to decrease following the Mediterranean diet application. While these findings require further exploration, they underscore the assay&#8217;s potential in <strong>nutrition studies, disease research, and clinical interventions.<\/strong><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Future Directions and Accessibility of MEGA<\/strong><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">In the future, the assay has the potential to become a standard tool in clinical research and metabolomics studies due to its compatibility with various mass spectrometry platforms and its ease of use. The team has prioritized making the assay accessible to laboratories worldwide, democratizing access to high-quality metabolomics data. By bridging gaps in metabolite analysis, the assay not only enhances research capabilities but also contributes to the broader goal of advancing precision medicine and personalized healthcare..<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">References<\/h2>\n\n\n\n<ol class=\"wp-block-list\">\n<li> Zhang, L.; Zheng, J.; Johnson, M.; Mandal, R.; Cruz, M.; Martinez-Hu\u00e9lamo, M.; Andres-Lacueva, C.; Wishart, D.S. A Comprehensive LC-MS Metabolomics Assay for Quantitative Analysis of Serum and Plasma. Metabolites 2024,&nbsp;<a href=\"https:\/\/doi.org\/10.3390\/metabo1411062214\">https:\/\/doi.org\/10.3390\/metabo1411062214<\/a>, 622.<\/li>\n\n\n\n<li>Cardelo, M.P.; Corina, A.; Leon-Acu\u00f1a, A.; Quintana-Navarro, G.M.; Alcala-Diaz, J.F.; Rangel-Zu\u00f1iga, O.A.; Camargo, A.; Conde-Gavilan, C.; Carmona-Medialdea, C.; Vallejo-Casas, J.A.; et al. Effect of the Mediterranean diet and probiotic supplementation in the management of mild cognitive impairment: Rationale, methods, and baseline characteristics. Front Nutr 2022, 9, 1037842, doi:10.3389\/fnut.2022.1037842.<\/li>\n\n\n\n<li>&nbsp;<a href=\"https:\/\/www.tmicwishartnode.ca\/product\/mtx-mega-assay-lc-ms-targeted-3\">https:\/\/www.tmicwishartnode.ca\/product\/mtx-mega-assay-lc-ms-targeted-3<\/a><\/li>\n<\/ol>\n\n<\/div>\n\t<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":3,"featured_media":4577,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[5],"tags":[],"class_list":["post-5169","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.ub.edu\/nutrimetabolomics\/wp-json\/wp\/v2\/posts\/5169","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.ub.edu\/nutrimetabolomics\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.ub.edu\/nutrimetabolomics\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.ub.edu\/nutrimetabolomics\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/www.ub.edu\/nutrimetabolomics\/wp-json\/wp\/v2\/comments?post=5169"}],"version-history":[{"count":1,"href":"https:\/\/www.ub.edu\/nutrimetabolomics\/wp-json\/wp\/v2\/posts\/5169\/revisions"}],"predecessor-version":[{"id":5170,"href":"https:\/\/www.ub.edu\/nutrimetabolomics\/wp-json\/wp\/v2\/posts\/5169\/revisions\/5170"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.ub.edu\/nutrimetabolomics\/wp-json\/wp\/v2\/media\/4577"}],"wp:attachment":[{"href":"https:\/\/www.ub.edu\/nutrimetabolomics\/wp-json\/wp\/v2\/media?parent=5169"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.ub.edu\/nutrimetabolomics\/wp-json\/wp\/v2\/categories?post=5169"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.ub.edu\/nutrimetabolomics\/wp-json\/wp\/v2\/tags?post=5169"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}