Publications
Nightingale Health’s technology is routinely used in world-class epidemiological and genetic studies. There are over 450 publications that have utilized our technology.
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
Inflammation
Metabolic risk factors
Circulating Polyunsaturated Fatty Acids and COVID-19: A Prospective Cohort Study and Mendelian Randomization Analysis
Sun et al. 2022. Frontiers in Medicine. Volume 9
Metabolic risk factors
Postprandial and Fasting Metabolic Signatures: Insights From the ZOE PREDICT 1 Study
Linenberg et al. Current Developments in Nutrition. 2022 Vol 6, Issue Supplement 1; 448
Cardiovascular diseases
Role of circulating polyunsaturated fatty acids on cardiovascular diseases risk: analysis using Mendelian randomization and fatty acid genetic association data from over 114,000 UK Biobank participants
Borges et al. BMC med. 2022 Jun 13;20(1):210
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
Human genetics
Whole-exome sequencing identifies rare genetic variants associated with human plasma metabolites
Bomba et al. Am J Hum Genet. 2022
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
Liu et al. Biomed Res Int. 2022
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
Cardiovascular diseases
Association of egg consumption, metabolic markers, and risk of cardiovascular diseases: A nested case-control study
Pan et al. Elife. 2022
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
Cardiovascular diseases
Association of Red Meat Consumption, Metabolic Markers, and Risk of Cardiovascular Diseases
Pan et al. Front Nutr. 2022