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
Bell et al 2019 bioRxiv; preprint
Metabolic risk factors
Metabolomics profile in depression: a pooled analysis of 230 metabolic markers in 5,283 cases with depression and 10,145 controls
Bot et al. Biol. Psychiatry 2019 Pre-print
Metabolic risk factors
Influence of puberty timing on adiposity and cardiometabolic traits: A Mendelian randomisation study
Bell et al. PLoS Medicine 2018;15(8):e1002641
Metabolic risk factors
Associations of Aerobic Fitness and Maximal Muscular Strength With Metabolites in Young Men
Kujala et al. JAMA Netw Open. 2019;2(8):e198265.
Maternal health
Maternal depression and inflammation during pregnancy
Lahti-Pulkkinen et al. Psychol Med. 2019:1-13
Metabolic risk factors
A metabolic profile of all-cause mortality risk identified in an observational study of 44,168 individuals
Deelen et al., NAT COMMUN 2019;10:3346
Cardiovascular diseases
A Plasma Proteogenomic Signature for Fibromuscular Dysplasia
Olin et al. Cardiovascular Research 2020; 116(1):63-77
Cardiovascular diseases
A Plasma Proteogenomic Signature for Fibromuscular Dysplasia
Olin et al. Cardiovasc Res. 2019 Pre-print
Locke et al. Nature 2019; Jul 31
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