Milk Metabolomics Data Reveal the Energy Balance of Individual Dairy Cows in Early Lactation

Research output: Contribution to journalArticleAcademicpeer-review

3 Citations (Scopus)

Abstract

In early lactation, dairy cows typically have a negative energy balance which has been related to metabolic disorders, compromised health and fertility, and reduced productive lifespan. Assessment of the energy balance, however, is not easy on the farm. Our aims were to investigate the milk metabolic profiles of dairy cows in early lactation, and to obtain models to estimate energy balance from milk metabolomics data and milk production traits. Milk samples were collected in week 2 and 7 after calving from 31 dairy cows. For each cow, the energy balance was calculated from energy intake, milk production traits and body weight. A total of 52 milk metabolites were detected using LC-QQQ-MS. Data from different lactation weeks was analysed by partial least squares analysis, the top 15 most relevant variables from the metabolomics data related to energy balance were used to develop reduced linear models to estimate energy balance by forward selection regression. Milk fat yield, glycine, choline and carnitine were important variables to estimate energy balance (adjusted R2: 0.53 to 0.87, depending on the model). The relationship of these milk metabolites with energy balance is proposed to be related to their roles in cell renewal.

Original languageEnglish
Article number15828
JournalScientific Reports
Volume8
DOIs
Publication statusPublished - 25 Oct 2018

Fingerprint

Metabolomics
Lactation
Milk
Metabolome
Carnitine
Choline
Energy Intake
Least-Squares Analysis
Glycine
Fertility
Linear Models
Fats
Body Weight
Health

Cite this

@article{fddcdf58fa7b49cb8f1b9a6ddc190ec2,
title = "Milk Metabolomics Data Reveal the Energy Balance of Individual Dairy Cows in Early Lactation",
abstract = "In early lactation, dairy cows typically have a negative energy balance which has been related to metabolic disorders, compromised health and fertility, and reduced productive lifespan. Assessment of the energy balance, however, is not easy on the farm. Our aims were to investigate the milk metabolic profiles of dairy cows in early lactation, and to obtain models to estimate energy balance from milk metabolomics data and milk production traits. Milk samples were collected in week 2 and 7 after calving from 31 dairy cows. For each cow, the energy balance was calculated from energy intake, milk production traits and body weight. A total of 52 milk metabolites were detected using LC-QQQ-MS. Data from different lactation weeks was analysed by partial least squares analysis, the top 15 most relevant variables from the metabolomics data related to energy balance were used to develop reduced linear models to estimate energy balance by forward selection regression. Milk fat yield, glycine, choline and carnitine were important variables to estimate energy balance (adjusted R2: 0.53 to 0.87, depending on the model). The relationship of these milk metabolites with energy balance is proposed to be related to their roles in cell renewal.",
author = "Wei Xu and Jacques Vervoort and Edoardo Saccenti and {van Hoeij}, Renny and Bas Kemp and {van Knegsel}, Ariette",
year = "2018",
month = "10",
day = "25",
doi = "10.1038/s41598-018-34190-4",
language = "English",
volume = "8",
journal = "Scientific Reports",
issn = "2045-2322",
publisher = "Nature Publishing Group",

}

Milk Metabolomics Data Reveal the Energy Balance of Individual Dairy Cows in Early Lactation. / Xu, Wei; Vervoort, Jacques; Saccenti, Edoardo; van Hoeij, Renny; Kemp, Bas; van Knegsel, Ariette.

In: Scientific Reports, Vol. 8, 15828, 25.10.2018.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - Milk Metabolomics Data Reveal the Energy Balance of Individual Dairy Cows in Early Lactation

AU - Xu, Wei

AU - Vervoort, Jacques

AU - Saccenti, Edoardo

AU - van Hoeij, Renny

AU - Kemp, Bas

AU - van Knegsel, Ariette

PY - 2018/10/25

Y1 - 2018/10/25

N2 - In early lactation, dairy cows typically have a negative energy balance which has been related to metabolic disorders, compromised health and fertility, and reduced productive lifespan. Assessment of the energy balance, however, is not easy on the farm. Our aims were to investigate the milk metabolic profiles of dairy cows in early lactation, and to obtain models to estimate energy balance from milk metabolomics data and milk production traits. Milk samples were collected in week 2 and 7 after calving from 31 dairy cows. For each cow, the energy balance was calculated from energy intake, milk production traits and body weight. A total of 52 milk metabolites were detected using LC-QQQ-MS. Data from different lactation weeks was analysed by partial least squares analysis, the top 15 most relevant variables from the metabolomics data related to energy balance were used to develop reduced linear models to estimate energy balance by forward selection regression. Milk fat yield, glycine, choline and carnitine were important variables to estimate energy balance (adjusted R2: 0.53 to 0.87, depending on the model). The relationship of these milk metabolites with energy balance is proposed to be related to their roles in cell renewal.

AB - In early lactation, dairy cows typically have a negative energy balance which has been related to metabolic disorders, compromised health and fertility, and reduced productive lifespan. Assessment of the energy balance, however, is not easy on the farm. Our aims were to investigate the milk metabolic profiles of dairy cows in early lactation, and to obtain models to estimate energy balance from milk metabolomics data and milk production traits. Milk samples were collected in week 2 and 7 after calving from 31 dairy cows. For each cow, the energy balance was calculated from energy intake, milk production traits and body weight. A total of 52 milk metabolites were detected using LC-QQQ-MS. Data from different lactation weeks was analysed by partial least squares analysis, the top 15 most relevant variables from the metabolomics data related to energy balance were used to develop reduced linear models to estimate energy balance by forward selection regression. Milk fat yield, glycine, choline and carnitine were important variables to estimate energy balance (adjusted R2: 0.53 to 0.87, depending on the model). The relationship of these milk metabolites with energy balance is proposed to be related to their roles in cell renewal.

U2 - 10.1038/s41598-018-34190-4

DO - 10.1038/s41598-018-34190-4

M3 - Article

VL - 8

JO - Scientific Reports

JF - Scientific Reports

SN - 2045-2322

M1 - 15828

ER -