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
Cross-sectional associations between Ideal Cardiovascular Health scores and vascular phenotypes in 11- to 12-year-olds and their parents: The Longitudinal Study of Australian Children
Liu et al. Int J Cardiol. 2019;277;258-265
Metabolic risk factors
Metabolic profling of adherence to diet, physical activity and body size recommendations for cancer prevention
Gu et al, Scientific Reports 2018;8:16293
Metabolic risk factors
Mendelian randomization reveals unexpected effects of CETP on the lipoprotein profile
Blauw et al, EJHG. 2018, doi:10.1038/s41431-018-0301-5
Thesing et al. Psychoneuroendocrinology 2018;97;206-215
Metabolic risk factors
What is ‘LDL cholesterol’?
Holmes and Ala-Korpela, Nature Reviews Cardiology (2019)
Human genetics
Trans-ancestry fine mapping and molecular assays identify regulatory variants at the ANGPTL8 HDL-C GWAS locus
Cannon et al. G3 (Bethesda) 2017;7(9)3217-3227
Fizelova et al. The Journal of Clinical Endocrinology & Metabolism 2017;102(9):3600–09
Cardiovascular diseases
Association of Genetic Variants Related to CETP Inhibitors and Statins With Lipoprotein Levels and Cardiovascular Risk
Ference et al. Journal of the American College of Cardiology 2017;318(10):947-56
Maternal health
Association of pre-pregnancy body mass index with offspring metabolic profile: Analyses of 3 European prospective birth cohorts
Santos Ferreira et al. PLoS Medicine 2017;14(8):e1002376
Cardiovascular diseases
Experimental and Human Evidence for Lipocalin‐2 (Neutrophil Gelatinase‐Associated Lipocalin [NGAL]) in the Development of Cardiac Hypertrophy and heart failure
Marques et al. Journal of the American Heart Association 2017;6(6):e005971
Bioinformatics
metaCCA: summary statistics-based multivariate meta-analysis of genome-wide association studies using canonical correlation analysis
Cichonska et al. Bioinformatics 2016;32(13):1981-89
Bioinformatics
Assessing multivariate gene-metabolome associations with rare variants using Bayesian reduced rank regression
Marttinen et al. Bioinformatics 2014;30(14):2026-34
Preiss et al. Diabetic Medicine 2016;33(11):1569-74
Würtz et al. International Journal of Epidemiology 2016;45(5):1493-506
Van de Rest et al. Aging 2016;8(1):111-24