Cohorts using Nightingale's data

Collaboration across multiple cohorts ensures convincing scientific results and enables faster translation. Analyze your findings with other cohorts to increase statistical power and publish highly reproducible science.

Numerous cohorts have already used Nightingale for metabolic profiling of projects, frequently at the whole cohort scale. Our technology provides data in absolute concentration units, with no batch effects. Therefore, it is straightforward to meta-analyze the data across different cohorts, replicate your findings and increase the statistical power of individual studies. Many scientific publications have proven that biomarkers associations based on Nightingale data are highly replicable across cohorts.

Nightingale encourages collaboration across multiple cohorts because such partnerships enable replication and validation of the key results. This ensures high-quality reproducible results and is often recommended for publication in the top journals. Eventually, this allows faster translation of the research findings into clinical use.

Ultimately, uncovering disease mechanisms and translating your findings to clinical context can help more people live healthier lives. To make such collaborations easier, we have listed below some of the cohorts that have Nightingale’s data available. To unleash the strengths of replicable biomarker results also for your data sets, we recommend you to reach out to the senior study author or study PI for collaboration requests. It is easy to replicate results using summary statistics whenever sharing individual person's data is challenging.

List of cohorts

Alzheimer's Disease Neuroimaging Initiative (ADNI)

Action in Diabetes and Vascular Disease: Preterax and Diamicron Modified Release Controlled Evaluation trial (ADVANCE trial)

Avon Longitudinal Study of Parents and Children (ALSPAC)

Bell et al. Journal of the American College of Cardiology 2018. https://www.jacc.org/doi/full/10.1016/j.jacc.2018.09.066

Almonds Trial Targeting Dietary Intervention with Snacks study (ATTIS)

Dikariyanto et al. The Americal Journal of Clinical Nutrition 2020. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7266688/

Barwon Infant Study

Ellul et al. Pediatric Research 2020. https://www.nature.com/articles/s41390-020-0762-4

Biobanking Netherlands BBMRI-NL

Including Rotterdam Study, the LifeLines-DEEP cohort, Growing Old Together Study, Netherlands Epidemiology of Obesity. https://www.bbmri.nl/Omics-metabolomics

British Regional Heart Study

Joshi et al. European Journal of Preventive Cardiology 2020. https://journals.sagepub.com/doi/10.1177/2047487319899621

British Women’s Heart and Health Study (BWHHS)

Borges et al. Circulation: Cardiovascular Genetics. 2017. https://www.ahajournals.org/doi/full/10.1161/CIRCGENETICS.117.001837

Born in Bradford

Taylor et al. Metabolites 2019. https://www.mdpi.com/2218-1989/9/9/190/htm

Carotid Atherosclerosis: Metformin for Insulin Resistance study (CAMERA)

Preiss et al. Diabetic Medicine 2016. https://onlinelibrary.wiley.com/doi/abs/10.1111/dme.13097

Cardiovascular Risk in Young Finns Study

Sliz et al. Human Molecular Genetics 2018. https://academic.oup.com/hmg/article/27/12/2214/4966855

China Kadoorie Biobank

Cooperative Health Research in the Region of Augsburg (KORA)

Copenhagen General Population Study

FinnDiane Study

Mäkinen et al. Journal of Internal Medicine 2013. https://onlinelibrary.wiley.com/doi/full/10.1111/joim.12026

FINRISK cohorts

HUNT study

INTERVAL trial

London Life Sciences Prospective Population Study (LOLIPOP)

Chambers et al. Lancet Diabetes Endocrinol 2015. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4724884/

Longitudinal Study of Australian Children

Wang et al. International Journal of Epidemiology 2019. https://academic.oup.com/ije/article/48/5/1556/5366222?login=true

Metabolic Syndrome In Men study (METSIM)

Gallois et al. Nature Communications 2019. https://www.nature.com/articles/s41467-019-12703-7

Northern Finland Birth Cohort 1966 and 1986

Prevención con Dieta Mediterránea PREDIMED+

Coltell et al. Nutrients 2020. https://www.mdpi.com/2072-6643/12/2/310/htm

Prevention of Renal and Vascular End-stage Disease Intervention Trial (PREVEND IT)

Kofink et al. Circulation: Genomic and Precision Medicine 2017. https://www.ahajournals.org/doi/full/10.1161/circgenetics.117.001759

PROspective Study of Pravastatin in the Elderly at Risk trial (PROSPER)

Delles et al. European journal of heart failure 2018. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5947152/

Prostate Testing for Cancer and Treatment (ProtecT)

Beynon et al. International Journal of Cancer 2018. https://onlinelibrary.wiley.com/doi/full/10.1002/ijc.31929

Singapore Multiethnic Cohort (MEC)

South Asia Biobank

Southall And Brent Revisited Study (SABRE)

Special Turku Coronary Risk Factor Intervention Project study (STRIP)

Lehtovirta et al. the Journal of Pediatrics 2018. https://www.jpeds.com/article/S0022-3476(17)31613-X/fulltext

TwinsUK, PREDICT study

Asnicaret al. Nature Medicine 2021. https://www.nature.com/articles/s41591-020-01183-8

United Kingdom Collaborative Trial of Ovarian Cancer Screening (UKCTOCS)

Borges et al. Circulation: Cardiovascular Genetics. 2017. https://www.ahajournals.org/doi/full/10.1161/CIRCGENETICS.117.001837

UK Pregnancies Better Eating and Activity Trial (UPBEAT)

Whitehall II study

Akbaraly et al. Scientific Reports 2018. https://www.nature.com/articles/s41598-018-26441-1

If you have profiled your cohort with Nightingale and would like to be added to this list to enhance your collaboration with this large research community, please contact us at: research[at]nightingalehealth.com.

Ready to place an order?