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
Blood metabolomic measures associate with present and future glycemic control in type 2 diabetes
Leen M't Hart et al. The Journal of Clinical Endocrinology & Metabolism 2018;103(12):4569-79.
Drug development
Metabolomic Consequences of Genetic Inhibition of PCSK9 Compared with Statin Treatment
Sliz et al. Circulation. 2018;138:2499–2512
Welsh et al. Diabetologia 2018;61(7):1581–91
Metabolic risk factors
Cholesteryl Ester Transfer Protein Influences High-Density Lipoprotein Levels and Survival in Sepsis
Trinder et al. American Journal of Respiratory and Critical Care Medicine 2019;199(7):854-62.
Human genetics
The effect of apolipoprotein E polymorphism on serum metabolome – a population-based 10-year follow-up study
Karjalainen et al. Scientific Reports 2019:9(458)
Bioinformatics
PhenoSpD: an integrated toolkit for phenotypic correlation estimation and multiple testing correction using GWAS summary statistics
Zheng et al. GigaScience 2018;7(8):1-10
Metabolic risk factors
Reduced plasma concentration of branched-chain amino acids in sarcopenic older subjects: a cross-sectional study
Ottestad et al. British Journal of Nutrition 2018;120:445–453
Cardiovascular diseases
CETP (Cholesteryl Ester Transfer Protein) Concentration A Genome-Wide Association Study Followed by Mendelian Randomization on Coronary Artery Disease
Blauw et al. Circ Genom Precis Med 2018;11:e002034
Cardiovascular diseases
Metabolic profiling of intra- and extracranial carotid artery atherosclerosis
Vojinovic et al. Atherosclerosis 2018;272:60-65
Cardiovascular diseases
Glycosylation Profile of Immunoglobulin G Is Cross-Sectionally Associated With Cardiovascular Disease Risk Score and Subclinical Atherosclerosis in Two Independent Cohorts
Menni et al. Circulation Research 2018;122(11):1555–64
Metabolic risk factors
Metabolic profiling of intra- and extracranial carotid artery atherosclerosis
Vojinovic et al. Atherosclerosis 2018;272:60-65
Human genetics
Identification of seven novel loci associated with amino acid levels using single variant and gene-based tests in 8,545 Finnish men
Teslovich et al. Human Molecular Genetics 2018;27(9):1664-74
Øyri et al. British Journal of Nutrition, 2018;119,(10):343-52
Vrieling et al. EBioMedicine 2018;32:192-200
Neurological diseases
The association of omega-3 fatty acid levels with personality and cognitive reactivity
Thesing et al. J Psychosom Res 2018;108;93-101