Publications
Nightingale’s technology is routinely used in world-class epidemiological and genetic studies. There are over 450 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
Bioinformatics
MiMIR: R-shiny application to infer risk factors and endpoints from Nightingale Health's 1H-NMR Metabolomics data
Bizzarri et al. Bioinformatics. 2022 Jun 13;38(15):3847–9
Cardiovascular diseases
The metabolic signature of cardiovascular disease and arterial calcification in patients with chronic kidney disease
Sørensen et al. 2022 Jun;350:109-118
Metabolic risk factors
Evaluation of the Value of Waist Circumference and Metabolomics in the Estimation of Visceral Adipose Tissue
Boone et al. American Journal of Epidemiology, Volume 191, Issue 5, May 2022, Pages 886–899
Metabolic risk factors
Association between mitochondrial DNA haplogroups J and K, serum branched-chain amino acids and lowered capability for endurance exercise
Kiiskilä et al. BMC Sports Sci Med Rehabil. 2022 May 26;14(1):95
Metabolic risk factors
Early life infection and proinflammatory, atherogenic metabolomic and lipidomic profiles at 12 months of age: a population-based cohort study
Mansell et al. Elife 2022
Bioinformatics
Gene-SCOUT: identifying genes with similar continuous trait fingerprints from phenome-wide association analyses
Middleton et al. 2022. Nucleic Acids Research, Volume 50, Issue 8, 6 May 2022, Pages 4289–4301
Metabolic risk factors
Investigating Causal Relations Between Circulating Metabolites and Alzheimer’s Disease: A Mendelian Randomization Study
Huang et al. J Alzheimers Dis. 2022;87(1):463-477
Drug development
Apolipoprotein A-V is a potential target for treating coronary artery disease: evidence from genetic and metabolomic analyses
Ibi et al. 2022. Journal of Lipid Research, Volume 63, Issue 5, 100193
Mäkinen et al. Int J Epidemiol. 2022 Apr 20:dyac062
Seah et al. J Clin Endocrinol Metab 2021
Metabolic risk factors
What characterizes event-free elderly FH patients? A comprehensive lipoprotein profiling
Melnes et al. Nutr Metab Cardiovasc Dis. 2022 Apr 5:S0939-4753(22)00148-X
Metabolic risk factors
Comprehensive biomarker profiling of hypertension in 36 985 Finnish individuals.
Palmu et al. J Hypertens. 2021.
Zarzar et al. Front Radiol. 2022;2:782864.
Maternal health
Maternal inflammatory and omega-3 fatty acid pathways mediate the association between socioeconomic disadvantage and childhood cognition
Marx et al. Brain Behav Immun. 2022 Feb;100:211-218
Gut microbiota
Metabolomic and microbiome profiling reveals personalized risk factors for coronary artery disease
Talmor-Barkan et al. Nat Med. 2022 Feb;28(2):295-302