**5. Conclusions**

In this study we used an untargeted 1H NMR metabolomics approach to investigate the serum metabolic fingerprints of the two most common biomarkers of energy balance in dairy cows, BHBA and NEFA. Our results sugges<sup>t</sup> that while BHBA and NEFA are indicative of similar metabolic states in early-lactation dairy cows, there are significant di fferences between the two biomarkers. Metabolites with common co-variances were intermediates of energy, phospholipid, and methyl donor metabolism. The most significant di fferences in the metabolomic fingerprints were related to acetate and creatine metabolism. We also identified several intermediate metabotypes which, when combined with genomic data, will enable further the investigation of the genetic architecture of metabolic health in early lactation dairy cows.

**Supplementary Materials:** The following are available online at http://www.mdpi.com/2218-1989/10/6/247/s1, Table S1: 1H NMR chemical shifts (δ) and multiplicity of metabolites in bovine serum run in deuterated water (D2O). Clearly observed resonances are indicated in bold text. s, singlet; d, doublet; dd, doublet of a doublet; m, multiplet; t, triplet. The right two columns show the direction of the relationship with serum β-hydroxybutyrate (BHBA) and non-esterified fatty acid (NEFA) concentrations determined by colorimetric assays, Table S2: Results of ANOVA-simultaneous component analysis (ASCA) of 1H NMR spectra of bovine serum ( *N*= 298). E ffect describes the relative influence of each variable (herd, age and days in milk (DIM)) on spectra. *p*-value is derived from permutation testing (1000 iterations), Figure S1: Results of PCA of 1H NMR spectra of serum obtained from 298 dairy cows in early lactation from the Ellinbank research farm (Dataset 1, *N* = 248) and a commercial dairy farm in Tasmania (Dataset 2, *N* = 50), Figure S2: VIP scores from OPLS regressions of 1H NMR spectra of serum obtained from 298 dairy cows in early lactation against (a) BHBA concentration and (b) NEFA concentration.

**Author Contributions:** Conceptualization, T.D.W.L., J.E.P., W.J.W., and S.J.R.; formal analysis, T.D.W.L. and S.J.R.; funding acquisition, J.E.P.; investigation, T.D.W.L. and S.J.R.; methodology, T.D.W.L. and S.J.R.; project administration, J.E.P., W.J.W. and S.J.R.; resources, S.J.R.; supervision, J.E.P., W.J.W., and S.J.R.; visualization, T.D.W.L.; writing—original draft, T.D.W.L.; writing—review and editing, T.D.W.L, J.E.P., W.J.W., and S.J.R. All authors have read and agreed to the published version of the manuscript.

**Funding:** DairyBio: jointly funded by Dairy Australia (Melbourne, Australia), the Gardiner Foundation (Melbourne, Australia), and Agriculture Victoria (Melbourne, Australia) funded this study and T.D.W.L.'s PhD project.

**Acknowledgments:** The authors thank Aaron Elkins and Simone Vassiliadis for assistance with 1H NMR protocol and metabolite identification, Di Mapleson, Brigid Ribaux and the sta ff at Ellinbank Dairy Research Centre (Ellinbank, Australia) for their technical expertise and assistance, Erika Oakes and the staff at Datagene (Bundoora, Australia) for their work coordinating this study, and the farmers who took part in this project.

**Conflicts of Interest:** The authors declare no conflict of interest.
