Literature DB >> 22098372

NMR metabolomic analysis of dairy cows reveals milk glycerophosphocholine to phosphocholine ratio as prognostic biomarker for risk of ketosis.

Matthias S Klein1, Nina Buttchereit, Sebastian P Miemczyk, Ann-Kathrin Immervoll, Caridad Louis, Steffi Wiedemann, Wolfgang Junge, Georg Thaller, Peter J Oefner, Wolfram Gronwald.   

Abstract

Ketosis is a common metabolic disease in dairy cows. Diagnostic markers for ketosis such as acetone and beta-hydroxybutyric acid (BHBA) are known, but disease prediction remains an unsolved challenge. Milk is a steadily available biofluid and routinely collected on a daily basis. This high availability makes milk superior to blood or urine samples for diagnostic purposes. In this contribution, we show that high milk glycerophosphocholine (GPC) levels and high ratios of GPC to phosphocholine (PC) allow for the reliable selection of healthy and metabolically stable cows for breeding purposes. Throughout lactation, high GPC values are connected with a low ketosis incidence. During the first month of lactation, molar GPC/PC ratios equal or greater than 2.5 indicate a very low risk for developing ketosis. This threshold was validated for different breeds (Holstein-Friesian, Brown Swiss, and Simmental Fleckvieh) and for animals in different lactations, with observed odds ratios between 1.5 and 2.38. In contrast to acetone and BHBA, these measures are independent of the acute disease status. A possible explanation for the predictive effect is that GPC and PC are measures for the ability to break down phospholipids as a fatty acid source to meet the enhanced energy requirements of early lactation.

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Year:  2011        PMID: 22098372     DOI: 10.1021/pr201017n

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  24 in total

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Authors:  Jennifer T Smilowitz; Aifric O'Sullivan; Daniela Barile; J Bruce German; Bo Lönnerdal; Carolyn M Slupsky
Journal:  J Nutr       Date:  2013-09-11       Impact factor: 4.798

2.  Comparative studies of two methods for miRNA isolation from milk whey.

Authors:  Xiao-lu Jin; Zi-hai Wei; Lan Liu; Hong-yun Liu; Jian-xin Liu
Journal:  J Zhejiang Univ Sci B       Date:  2015-06       Impact factor: 3.066

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Authors:  Christian Heiss; Zhirui Wang; Ian Black; Parastoo Azadi; Raina N Fichorova; Bibhuti N Singh
Journal:  Carbohydr Res       Date:  2015-11-10       Impact factor: 2.104

4.  Plasma metabolomic profiling of dairy cows affected with ketosis using gas chromatography/mass spectrometry.

Authors:  Hongyou Zhang; Ling Wu; Chuang Xu; Cheng Xia; Lingwei Sun; Shi Shu
Journal:  BMC Vet Res       Date:  2013-09-26       Impact factor: 2.741

5.  Integrating milk metabolite profile information for the prediction of traditional milk traits based on SNP information for Holstein cows.

Authors:  Nina Melzer; Dörte Wittenburg; Dirk Repsilber
Journal:  PLoS One       Date:  2013-08-21       Impact factor: 3.240

6.  NMR-Based Milk Metabolomics.

Authors:  Ulrik K Sundekilde; Lotte B Larsen; Hanne C Bertram
Journal:  Metabolites       Date:  2013-04-02

7.  Applications of NMR in dairy research.

Authors:  Anthony D Maher; Simone J Rochfort
Journal:  Metabolites       Date:  2014-03-04

8.  Choline and choline metabolite patterns and associations in blood and milk during lactation in dairy cows.

Authors:  Virginia M Artegoitia; Jesse L Middleton; Federico M Harte; Shawn R Campagna; Michael J de Veth
Journal:  PLoS One       Date:  2014-08-26       Impact factor: 3.240

9.  Gene-based mapping and pathway analysis of metabolic traits in dairy cows.

Authors:  Ngoc-Thuy Ha; Josef Johann Gross; Annette van Dorland; Jens Tetens; Georg Thaller; Martin Schlather; Rupert Bruckmaier; Henner Simianer
Journal:  PLoS One       Date:  2015-03-19       Impact factor: 3.240

10.  SMolESY: an efficient and quantitative alternative to on-instrument macromolecular 1H-NMR signal suppression.

Authors:  Panteleimon G Takis; Beatriz Jiménez; Caroline J Sands; Elena Chekmeneva; Matthew R Lewis
Journal:  Chem Sci       Date:  2020-05-27       Impact factor: 9.825

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