Literature DB >> 25691689

Quantitative serum nuclear magnetic resonance metabolomics in cardiovascular epidemiology and genetics.

Pasi Soininen1, Antti J Kangas1, Peter Würtz1, Teemu Suna1, Mika Ala-Korpela2.   

Abstract

Metabolomics is becoming common in epidemiology due to recent developments in quantitative profiling technologies and appealing results from their applications for understanding health and disease. Our team has developed an automated high-throughput serum NMR metabolomics platform that provides quantitative molecular data on 14 lipoprotein subclasses, their lipid concentrations and composition, apolipoprotein A-I and B, multiple cholesterol and triglyceride measures, albumin, various fatty acids as well as on numerous low-molecular-weight metabolites, including amino acids, glycolysis related measures and ketone bodies. The molar concentrations of these measures are obtained from a single serum sample with costs comparable to standard lipid measurements. We have analyzed almost 250 000 samples from around 100 epidemiological cohorts and biobanks and the new international set-up of multiple platforms will allow an annual throughput of more than 250 000 samples. The molecular data have been used to study type 1 and type 2 diabetes etiology as well as to characterize the molecular reflections of the metabolic syndrome, long-term physical activity, diet and lipoprotein metabolism. The results have revealed new biomarkers for early atherosclerosis, type 2 diabetes, diabetic nephropathy, cardiovascular disease and all-cause mortality. We have also combined genomics and metabolomics in diverse studies. We envision that quantitative high-throughput NMR metabolomics will be incorporated as a routine in large biobanks; this would make perfect sense both from the biological research and cost point of view - the standard output of over 200 molecular measures would vastly extend the relevance of the sample collections and make many separate clinical chemistry assays redundant.
© 2015 American Heart Association, Inc.

Entities:  

Keywords:  genetics; lipoprotein; metabolism; metabolomics; risk assessment

Mesh:

Year:  2015        PMID: 25691689     DOI: 10.1161/CIRCGENETICS.114.000216

Source DB:  PubMed          Journal:  Circ Cardiovasc Genet        ISSN: 1942-3268


  226 in total

1.  A plasma proteogenomic signature for fibromuscular dysplasia.

Authors:  Jeffrey W Olin; Antonio F Di Narzo; Valentina d'Escamard; Daniella Kadian-Dodov; Haoxiang Cheng; Adrien Georges; Annette King; Allison Thomas; Temo Barwari; Katherine C Michelis; Rihab Bouchareb; Emir Bander; Anelechi Anyanwu; Paul Stelzer; Farzan Filsoufi; Sander Florman; Mete Civelek; Stephanie Debette; Xavier Jeunemaitre; Johan L M Björkegren; Manuel Mayr; Nabila Bouatia-Naji; Ke Hao; Jason C Kovacic
Journal:  Cardiovasc Res       Date:  2020-01-01       Impact factor: 10.787

2.  Metabolomics technology and bioinformatics for precision medicine.

Authors:  Rajeev K Azad; Vladimir Shulaev
Journal:  Brief Bioinform       Date:  2019-11-27       Impact factor: 11.622

Review 3.  Recent Advances in NMR-Based Metabolomics.

Authors:  G A Nagana Gowda; Daniel Raftery
Journal:  Anal Chem       Date:  2016-12-02       Impact factor: 6.986

Review 4.  The genetics of drug efficacy: opportunities and challenges.

Authors:  Matthew R Nelson; Toby Johnson; Liling Warren; Arlene R Hughes; Stephanie L Chissoe; Chun-Fang Xu; Dawn M Waterworth
Journal:  Nat Rev Genet       Date:  2016-03-14       Impact factor: 53.242

Review 5.  The use of mass spectrometry for analysing metabolite biomarkers in epidemiology: methodological and statistical considerations for application to large numbers of biological samples.

Authors:  Mads V Lind; Otto I Savolainen; Alastair B Ross
Journal:  Eur J Epidemiol       Date:  2016-05-26       Impact factor: 8.082

6.  The Rotterdam Study: 2018 update on objectives, design and main results.

Authors:  M Arfan Ikram; Guy G O Brusselle; Sarwa Darwish Murad; Cornelia M van Duijn; Oscar H Franco; André Goedegebure; Caroline C W Klaver; Tamar E C Nijsten; Robin P Peeters; Bruno H Stricker; Henning Tiemeier; André G Uitterlinden; Meike W Vernooij; Albert Hofman
Journal:  Eur J Epidemiol       Date:  2017-10-24       Impact factor: 8.082

7.  Short-term interval training alters brain glucose metabolism in subjects with insulin resistance.

Authors:  Sanna M Honkala; Jarkko Johansson; Kumail K Motiani; Jari-Joonas Eskelinen; Kirsi A Virtanen; Eliisa Löyttyniemi; Juhani Knuuti; Pirjo Nuutila; Kari K Kalliokoski; Jarna C Hannukainen
Journal:  J Cereb Blood Flow Metab       Date:  2017-09-29       Impact factor: 6.200

8.  Mendelian randomization reveals unexpected effects of CETP on the lipoprotein profile.

Authors:  Lisanne L Blauw; Raymond Noordam; Sebastian Soidinsalo; C Alexander Blauw; Ruifang Li-Gao; Renée de Mutsert; Jimmy F P Berbée; Yanan Wang; Diana van Heemst; Frits R Rosendaal; J Wouter Jukema; Dennis O Mook-Kanamori; Peter Würtz; Ko Willems van Dijk; Patrick C N Rensen
Journal:  Eur J Hum Genet       Date:  2018-11-12       Impact factor: 4.246

Review 9.  Mendelian randomization in cardiometabolic disease: challenges in evaluating causality.

Authors:  Michael V Holmes; Mika Ala-Korpela; George Davey Smith
Journal:  Nat Rev Cardiol       Date:  2017-06-01       Impact factor: 32.419

Review 10.  Nuclear magnetic resonance spectroscopy as a new approach for improvement of early diagnosis and risk stratification of prostate cancer.

Authors:  Bo Yang; Guo-Qiang Liao; Xiao-Fei Wen; Wei-Hua Chen; Sheng Cheng; Jens-Uwe Stolzenburg; Roman Ganzer; Jochen Neuhaus
Journal:  J Zhejiang Univ Sci B       Date:  2017 Nov.       Impact factor: 3.066

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.