Baets, B., De

Fievez, V.

Jorjong, S.

Kemp, B.

Knegsel, A., van

Verwaeren, J.

Name not available

Validation of a predictive model for diagnosis of high concentration of plasma non-esterified fatty acids and subclinical ketosis in dairy cows

Wageningen Yield 

Validation of a predictive model for diagnosis of high concentration of plasma  
non-esterified fatty acids and subclinical ketosis in dairy cows 
 
S. Jorjong, A. T. M. van Knegsel , J. Verwaeren, B. De Baets, B. Kemp, V. Fievez 
 
1 Laboratory for Animal Nutrition and Animal Product Quality, Faculty of Bioscience Engineering, 
Ghent University, Proefhoevestraat 10, 9090 Melle, Belgium 
2 Adaptation Physiology Group, Department of Animal Science, Wageningen University, P.O. Box 
338, 6700 AH Wageningen, The Netherlands  
3 KERMIT, Department of Mathematical Modelling, Statistics and Bioinformatics, Ghent University, 
Coupure links 653, 9000 Ghent, Belgium 
 
 
Introduction 
 
Subclinical ketosis (SCK) is considered as a critical physiological disorder in dairy cows, as it is 
associated with reduced reproductive performance1. In addition, a severe negative energy balance 
(NEB), indicated by elevated plasma non-esterified fatty acids (NEFA), increases the risk for 
displaced abomasum, clinical ketosis, metritis, retained placenta, and it seems detrimental for dairy 
cow fertility2. Analysis of key blood metabolites, i.e. β-hydroxybutyrate (BHBA) and NEFA is 
considered the gold standard to diagnose SCK and severe NEB, respectively. However, monitoring of 
blood metabolites is invasive towards the cow. Hence, non-invasive milk tests are of high interest. In 
a previous study, we identified the milk fat (MF) C18:1 cis-9/C15:0 ratio and MF C18:1 cis-9 
concentration as potential biomarkers of SCK and high blood plasma NEFA, respectively3. The aim 
of the current study was to validate the quality of the formerly developed diagnostic models using an 
independent dataset. 
 
Material and Methods 
 
In the former study, thresholds were established for the milk biomarkers to diagnose SCK or elevated 
blood NEFA. For this, a dataset with blood and associated milk samples were classified based on 
either blood plasma BHBA (≥ or < 0.8 mmol/L) to diagnose at risk or not for SCK or NEFA (≥ or < 
0.6 mmol/L) to diagnose severe or mild NEB. A MF C18:1 cis-9/C15:0 ratio of 28 and a MF C18:1 
cis-9 concentration of 23 allowed for a maximum false positive (FP) rate of 10%, for diagnosis of 
SCK and elevated blood plasma NEFA, respectively. 
The current dataset was obtained from 93 cows (n = 372) in early lactation from Wageningen 
University Research Centre, the Netherlands. Cows were fed either a glucogenic or lipogenic diet and 
subjected to one of the three dry period management strategies (0, 30 or 60 days). Milk samples were 
collected in weeks 2, 3, 4 and 8 of lactation and analyzed for milk fatty acids, which were expressed 
as grams per 100 grams of fatty acid methyl esters. Blood samples were collected in weeks 2 to 8 of 
lactation for BHBA and NEFA analysis. To validate the MF thresholds, the dataset was split twice 
into two groups based on plasma BHBA and NEFA reference values (1.2 mmol/L and 0.6 mmol/L, 
respectively), for diagnosis of SCK and elevated blood plasma NEFA, respectively. Validation of the 
thresholds identified in the former study is illustrated in Table 1.  
 
Table 1. Identification of true positive (TP), true negative (TN), false positive (FP), and false negative 
(FN) cases for diagnosis of subclinical ketosis (SCK) and elevated blood plasma NEFA  
 
SCK BHBA≥1.2 BHBA<1.2 Elevated blood 
plasma NEFA 
NEFA≥0.6 NEFA<0.6 
*C18:1 cis-9/C15:0 ≥ 28 TP FP **C18:1 cis-9 ≥ 23 TP FP 
 C18:1 cis-9/C15:0 < 28 FN TN   C18:1 cis-9 < 23 FN TN 
* ratio C18:1 cis-9/C15:0 in milk fat, ** milk fat concentration of C18:1 cis-9, BHBA: plasma β-hydroxybutyrate, 
NEFA: plasma non-esterified fatty acids  
 
From the criteria mentioned in Table 1, the sensitivity (Se), specificity (sp), positive predictive value 
(PPV), negative predictive value (NPV), and accuracy can be calculated:  
Se = TP/(TP+FN); Sp = TN/(TN+FP); PPV = TP/(TP+FP); NPV = TN/(TN+FN);  
Accuracy = (TP+TN)/(TP+TN+FP+FN) 
 
Results and Discussion 
 
The prevalence of SCK and detrimental blood plasma NEFA in the current dataset was 20% (n = 73) 
and 12% (n = 45), respectively. A PPV of 40% for SCK diagnosis (Table 2) indicates that a cow with 
a positive test (i.e. MF C18:1 cis-9/C15:0 ≥ 28) has a 40% chance of having SCK. On the other hand, 
a NPV of 98% means that cows for which the test was negative (i.e. MF C18:1 cis-9/C15:0 < 28) only 
has a 2% chance of suffering from SCK. Similarly, the NPV of 94% for elevated blood plasma NEFA 
diagnosis indicates only 6% of the animals having a negative test (i.e. MF C18:1 cis-9 < 23) are 
having a high plasma NEFA concentration (> 0.6 mmol/L).  
 
Table 2. Validation of diagnosis test based on milk fatty acids 
  
Disorder Se  Sp   PPV NPV Accuracy 
*SCK  93 66 40 98 72 
**Elevated blood plasma NEFA  69 68 23 94 68 
Milk biomarker threshold values:* C18:1 cis-9/C15:0 = 28, **C18:1 cis-9 = 23 
 
Diagnosis of SCK based on MF C18:1 cis-9/C15:0 resulted in Se and Sp of 93% and 66%, 
respectively, with an overall accuracy of 72%. The Se of a test indicates the proportion of animals 
identified to suffer from SCK based on the MF biomarker relative to the total number of SCK 
diagnosed cows based on the blood reference value. Meanwhile, Sp indicates the proportion of 
healthy animals, based on the MF biomarker, relative to the total number of healthy cows, based on 
the blood reference threshold. 
 
Elevated blood plasma NEFA, diagnosed based on MF C18:1 cis-9, showed a Se and Sp of 69% and 
68%, respectively, with an overall accuracy of 68%. The difference in Se between diagnosis of SCK 
and elevated blood plasma NEFA indicates that the model for elevated blood plasma NEFA performs 
worse than the SCK model.  
 
In conclusion, validation of the formerly developed diagnostic models confirms the ratio C18:1 cis-9 
to C15:0 in milk fat is a promising biomarker for detection of subclinical ketosis in dairy cows. 
 
Acknowledgement 
Research was supported by an International co-ordinated action of the Fund for Scientific Research-
Flanders (Belgium). 
 
Reference  
1. Walsh, R.B., J.S. Walton, D.F. Kelton, S.J. LeBlanc, K.E. Leslie, and T.F. Duffield. 2007. 
The effect of subclinical ketosis in early lactation on reproductive performance of postpartum 
dairy cows. J. Dairy Sci. 0:2788-2796. 
2. Ospina, P.A., D.V. Nydam, T. Stokol, and T.R. Overton. 2010. Evaluation of non-esterified 
fatty acids and β-hydroxybutyrate in transition dairy cattle in the northeastern United States: 
Critical threshold for prediction of clinical disease. J. Dairy Sci. 93:546-554. 
3. Jorjong, S., A.T.M. van Knegsel, J. Verwaeren, M. Val Lahoz, B. De Baets, B. Kemp, R.M. 
Bruckmaier, and V. Fievez. 2014. Milk fatty acids as possible biomarkers to early diagnose 
high concentration of blood plasma non-esterified fatty acids and subclinical ketosis in dairy 
cows. J. Dairy Sci. (submitted). 
 


Validation of a predictive model for diagnosis of high concentration of plasma non-esterified fatty acids and subclinical ketosis in dairy cows

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