Publications
Nightingale’s technology is routinely used in world-class epidemiological and genetic studies. There are over 350 publications that have utilized our technology. If you are interested in using our technology for medical research, visit our website for researchers here.
All
Ageing
Bioinformatics
Cancer
Cardiovascular diseases
Drug development
Fatty liver disease
Gut microbiota
Human genetics
Kidney disease
Maternal health
Metabolic risk factors
Method description
Neurological diseases
Nutrition
T1D
T2D
Metabolic risk factors
Lifestyle-intervention-induced reduction of abdominal fat is reflected by a decreased circulating glycerol level and an increased HDL diameter
Beekman et al. BioRxiv 2019; preprint
Metabolic risk factors
Metabolomics: population epidemiology and concordance in Australian children aged 11-12 years and their parents
Ellul et al. BMJ Open 2019 Jul 4;9(Suppl 3):106-117
Cardiovascular diseases
Direct Estimation of HDL-Mediated Cholesterol Efflux Capacity From Serum
Kuusisto et al. Clin Chem. 2019 Pre-print
Method description
Assessment of reproducibility and biological variability of fasting and postprandial plasma metabolite concentrations using 1H NMR spectroscopy
Li-Gao et al. PLoS One 2019;14(6):e0218549
Hansson et al. British Journal of Nutrition 2019; preprint
Human genetics
The genomic architecture of blood metabolites based on a decade of genome-wide analyses
Hagenbeek et al. BioRxiv 2019 Pre-print
Juonala et al. J Am Heart Assoc. 2019;16;8(14):e011852
Sarin et al. Am J Clin Nutr. 2019;110(1):233-45
Davis et al. Atherosclerosis 2019;285:93–101
Cardiovascular diseases
A third of nonfasting plasma cholesterol is in remnant lipoproteins: Lipoprotein subclass profiling in 9293 individuals
Balling et al. Atherosclerosis 2019;286:97-104
Human genetics
Genetic Determinants of Circulating Glycine Levels and Risk of Coronary Artery Disease
Jia et al. Journal of the American Heart Association 2019;8(10):e011922
van den Akker et al. BioRxiv 2019 Pre-print
Metabolic risk factors
Sex and puberty-related differences in metabolomic profiles associated with adiposity measures in youth with obesity
Saner et al. Metabolomics 2019;15(5):75
Gut microbiota
Relationship between gut microbiota and circulating metabolites in population-based cohorts
Vojinovic et al. BioRxiv 2019 Pre-print
Metabolic risk factors
Metabolomics Profiling of Visceral Adipose Tissue: Results From MESA and the NEO Study
Neeland et al. Journal of American Heart Association 2019;8(9):e010810.