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In some past researches, the exploration for pathogenesis of ketosis mainly focuses on physiology,biochemistry and pathology.However, there is little report about the metabolomics of ketosis.Therefore, this report has an important significance in this study to reveal the global change of life functions during the development of ketosis, enrich and develop the its pathogenesis.Ketosis is a metabolic disorder in dairy cattle.Primary or secondary ketosis can result during early lactation.Generally, high milk production during lactation and/or inadequate energy intakes result in a negative energy balance, which induces ketosis.Because ketosis can lead to substantial economic losses in the dairy industry, it is of outmost importance to prevent ketosis in dairy cattle.Through the application of metabolomics technology combines principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA), changes of endogenous metabolites with clinical and subclinical ketosis cows were analyzed,which to study the affects of ketosis on cow metabolic process, and find the differences metabolites.In this study,80 lactation Holstein cows were selected as experimental animals 7 to 21 days postpartum, at the same time experimental cow plasma samples were collected according to the plasma β-hydroxybutyrate (BHBA)concentration and clinical symptoms.Clinical ketosis groups of cows (CK, n =24) showed obvious clinical symptoms postpartum and plasma BHBA concentration is more than 1.60 mmol/L, subclinical ketosis groups of cows (SK, n =33) didnt show clinical symptoms postpartum and plasma BHBA concentration is more than 1.20 mmol/L;healthy groups of cows (C, n =23) had no clinical symptoms and plasma BHBA concentration is less than 1.00 mmol/L.Experimental animals selected had no other concurrency and secondary diseases in addition to ketosis.The plasma metabolites were detected by1H nuclear magnetic resonance (1H NMR) and gas chromatography/mass spectrometry (GC/MS) technique.Changes of metabolite contents were analyzed among 3 groups using principal component analysis and partial lease squares.Finally, metabolites were analyzed by using bioinformatics technology biology.The plasma metabolic profiles of the three groups were obtained by1 H NMR.Compared with the healthy control group, 23 different metabolites were obtained in subclinical and clinical ketosis groups, in which Acetylacetonate (ACAC), β-hydroxybutyric acid (BHBA), acetone and acetic acid, etc are increased, while histidine, lysine, glutamic acid, glutamine, lactic acid and glucose, etc are decreased.By comparison, 28 different metabolites were obtained between clinical ketosis group and subclinical ketosis group,in which BHBA, ACAC,and acetone, etc are increased, while citric acid, formic acid, histidine, alanine, proline, tyrosine, low density lipoprotein, and very low density lipoprotein, etc are decreased.The plasma metabolome was measured by GC/MS,which led to the detection of 267 variables.There were 40 types of metabolites without difference among 3 groups.Compared with the healthy control group ,32 different metabolites were obtained in subclinical and clinical ketosis groups, in which BHBA, α-aminobutyric acid, sitoesterol, isoleucine, leucine, glycine, myristic acid and palmitic acid, etc are increased, while glucose, lactose, glyoxylic acid, alanine, glutamic acid, lactic acid, etc are decreased.By comparison, 13 different metabolites were obtained between clinical ketosis group and subclinical ketosis group, in which heptadecanoic acid, stearic acid and 3-hydroxy valeric acid, etc are increased, while proline, serine, proline, α-aminobutyric acid and 3,4-docosahexaenoic acid ,etc are decreased.Through the KEGG database analysis, these metabolites primarily were related with amino acid metabolism, fat metabolism and carbohydrate metabolism.The results showed 1H NMR and GC/MS combined with pattern recognition technique can effectively get the different metabolites of diagnosing clinical and subclinical ketosis.The substances of different content and contributing to classification may be the potential metabolic marker and objective indicators for diagnosing as ketosis, and panoramic reveal that widely metabolic disorder on cows in the process of ketosis, which lays the foundation for the exploration of ketosis mechanism and obtaining new biomarkers in the future.