Publications

Nightingale’s biomarker analysis platform is routinely used in world-class epidemiological and genetic studies. There are over 300 publications that have applied our method. See full list of publications here.

All

Metabolic risk factors

Metabolic biomarker profiling for identification of susceptibility to severe pneumonia and COVID-19 in the general population

Nightingale's blood biomarkers were used for prediction of severe pneumonia and COVID-19 hospitalisation in 105,146 plasma samples collected in the UK Biobank during 2007-2010.

Julkunen et al, ELife 2021

T2D

Circulating metabolic biomarkers are consistently associated with incident type 2 diabetes in Asian and European populations – a metabolomics analysis in five prospective cohorts

Hoong Seah et al, medRxiv 2021

T1D

Urinary metabolite profiling and risk of progression of diabetic nephropathy in 2670 individuals with type 1 diabetes

Mutter et al, Diabetologia 2021

T2D

Predictive value of circulating NMR metabolic biomarkers for type 2 diabetes risk in the UK Biobank study

Bragg et al, medRxiv 2021

Human genetics

Metabolomic signatures of lipid-modifying therapies using drug target Mendelian randomization

Richardson et al, medRxiv 2021

T2D

Plasma fatty acids and the risk of vascular disease and mortality outcomes in individuals with type 2 diabetes: results from the ADVANCE study

Harris et al. Diabetologia 2020

Drug development

Metabolic profiling of angiopoietin-like protein 3 and 4 inhibition: a drug-target Mendelian randomization analysis

Wang et al, European Heart Journal 2021

Cardiovascular diseases

VLDL Cholesterol Accounts for One-Half of the Risk of Myocardial Infarction Associated With apoB-Containing Lipoproteins

Balling et al, J Am Coll Cardiol 2020

Metabolic risk factors

The metabolic fingerprint of COVID-19 severity

Dierckx et al, medRxiv 2020

Cardiovascular diseases

Metabolic Biomarkers for Peripheral Artery Disease Compared with Coronary Artery Disease

Tikkanen et al, medRxiv 2020

Method description

Quantitative Serum Nuclear Magnetic Resonance Metabolomics in Cardiovascular Epidemiology and Genetics

Soininen et al. Circulation Cardiovascular Genetics 2015;8(1):192-206

Bioinformatics

High-throughput multivariable Mendelian randomization analysis prioritizes apolipoprotein B as key lipid risk factor for coronary artery disease

Zuber et al. MedRxiv 2020; preprint

Bioinformatics

Cross-platform genetic discovery of small molecule products of metabolism and application to clinical outcomes

Lotta et al. BioRxiv 2020; preprint

Metabolic risk factors

Triglyceride-containing lipoprotein sub-fractions and risk of coronary heart disease and stroke: A prospective analysis in 11,560 adults

Joshi et al. Eur J Prev Cardiol. 2020; preprint

Nutrition

Genome-Wide Association Study for Serum Omega-3 and Omega-6 Polyunsaturated Fatty Acids: Exploratory Analysis of the Sex-Specific Effects and Dietary Modulation in Mediterranean Subjects with Metabolic Syndrome

Coltell et al. Nutrients 2020;12(2):E310

Metabolic risk factors

Sex differences in infant blood metabolite profile in association with weight and adiposity measures

Ellul et al. Pediatr Res. 2020; preprint

Bioinformatics

EpiMetal: an open-source graphical web browser tool for easy statistical analyses in epidemiology and metabolomics

Ekholm et al. Int J Epidemiol. 2020; preprint