Data from: Metabolic changes associated with two endocrine abnormalities in dogs: elevated fructosamine and low thyroxine
Cite this dataset
Ottka, Claudia et al. (2022). Data from: Metabolic changes associated with two endocrine abnormalities in dogs: elevated fructosamine and low thyroxine [Dataset]. Dryad. https://doi.org/10.5061/dryad.tb2rbp031
Metabolomics studies in canine endocrine abnormalities are sparse and basic information on these abnormalities must be generated. This dataset includes the 1H NMR metabolic profiling results of 151 dog serum samples. The samples have been collected in an ethical way, being leftovers of clinical diagnostic samples. The sample set includes 25 control samples based on unremarkable routine clinical chemistry and hematology, 79 samples exhibiting high fructosamine which reflects poor glycemic control, and 47 samples with low thyroxine, a metabolically important thyroid hormone.
The metabolite data and metadata were utilized in the study: Ottka et al. Metabolic changes associated with two endocrine abnormalities in dogs: elevated fructosamine and low thyroxine.
The control group results were utilized also in: Ottka et al. Serum NMR metabolomics uncovers multiple metabolic changes in phenobarbital-treated dogs.
The dataset includes the unprocessed metabolite data in original units. The used samples are leftovers of canine clinical diagnostic serum samples submitted to a veterinary laboratory provider (LABOKLIN GmbH & Co KG, Bad Kissingen, Germany).
Metabolite data was generated using a validated canine nuclear magnetic resonance (NMR) spectroscopy metabolomics platform that quantifies 123 measurands (Ottka, Vapalahti, et al. 2021). The method is described elsewhere in further detail (Ottka, Vapalahti, et al. 2021; Soininen et al. 2009; Würtz et al. 2017). Briefly, the method utilizes a Bruker AVANCE III HD 500MHz NMR spectrometer with a 5 mm triple-channel (1H, 13C, 15N) z-gradient Prodigy probe head and SampleJet (Bruker Corp., Billerica, Massachusetts, USA) as the sample charger. Sample preparation includes light mixing of the sample, removal of possible precipitate, sample transfer to an NMR tube and mixing with sodium phosphate buffer using a PerkinElmer JANUS Automated Workstation with an 8-tip dispense arm with Varispan (PerkinElmer Inc., Waltham, Massachusetts, USA). Two NMR spectra are acquired automatically: the LIPO and LMWM windows; the LIPO window comprising a conventional water-suppressed 1H NMR spectrum with resonances from macromolecules and lipids, whereas the LMWM window uses T2-relaxation-filtering and is used for the detection of low-molecular-weight metabolites (Soininen et al. 2009). The NMR spectra are automatically processed with background control, baseline removal, and signal alignments, and absolute metabolite concentrations are obtained with a proprietary software that bases on regression modeling, and has integrated quality control (Würtz et al. 2017).
Ottka, C., Vapalahti, K., Puurunen, J., Vahtera, L., & Lohi, H. (2021). A novel canine nuclear magnetic resonance spectroscopy-based metabolomics platform: Validation and sample handling. Veterinary Clinical Pathology, n/a(50), 410–426. https://doi.org/https://doi.org/10.1111/vcp.12954
Soininen, P., Kangas, A. J., Wurtz, P., Tukiainen, T., Tynkkynen, T., Laatikainen, R., et al. (2009). High-throughput serum NMR metabonomics for cost-effective holistic studies on systemic metabolism. The Analyst, 134(9), 1781–1785. https://doi.org/10.1039/b910205a
Würtz, P., Kangas, A. J., Soininen, P., Lawlor, D. A., Davey Smith, G., & Ala-Korpela, M. (2017). Quantitative Serum Nuclear Magnetic Resonance Metabolomics in Large-Scale Epidemiology: A Primer on -Omic Technologies. American Journal of Epidemiology, 186(9), 1084–1096. https://doi.org/10.1093/aje/kwx016
See the README file for further information on this dataset. Missing values are expressed as blank cells.