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

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.

Detection of autosomal dominant polycystic kidney disease by NMR spectroscopic fingerprinting of urine.

Autosomal dominant polycystic kidney disease (ADPKD) is a frequent cause of kidney failure; however, urinary biomarkers for the disease are lacking. In a step towards identifying such markers, we used multidimensional-multinuclear nuclear magnetic resonance (NMR) spectroscopy with support vector machine-based classification and analyzed urine specimens of 54 patients with ADPKD and slightly reduced estimated glomerular filtration rates. Within this cohort, 35 received medication for arterial hypertension and 19 did not. The results were compared with NMR profiles of 46 healthy volunteers, 10 ADPKD patients on hemodialysis with residual renal function, 16 kidney transplant patients, and 52 type 2 diabetic patients with chronic kidney disease. Based on the average of 51 out of 701 NMR features, we could reliably discriminate ADPKD patients with moderately advanced disease from ADPKD patients with end-stage renal disease, patients with chronic kidney disease of other etiologies, and healthy probands with an accuracy of >80%. Of the 35 patients with ADPKD receiving medication for hypertension, most showed increased excretion of proteins and also methanol. In contrast, elevated urinary methanol was not found in any of the control and other patient groups. Thus, we found that NMR fingerprinting of urine differentiates ADPKD from several other kidney diseases and individuals with normal kidney function. The diagnostic and prognostic potential of these profiles requires further evaluation.