About
Biomarkers measured from blood samples are indicative of the risk for many chronic diseases, such as heart disease and diabetes. We intend to measure blood samples from the entire UK Biobank using a novel technology developed by Nightingale Health Ltd that captures >200 biomarker measures, such as lipids and amino acids, from each blood sample. Data analyses will assess how well these biomarker measures can predict future risk for disease onset. The analyses further aim to clarify the molecular roles of the biomarkers in chronic diseases and underlying risk factors, and clarify genetic and lifestyle contributions to the biomarker levels. The results may improve the ability to predict disease onset, which would allow better targeting of prevention efforts. The detailed metabolic profiling also provides an enhanced understanding of the molecular mechanisms leading to onset and progression of chronic diseases, and may hereby identify causal biomarkers and targets for drug treatment. The resource of >200 metabolic biomarker measures will also benefit numerous other research projects, such as studies of molecular intermediates of diet and other lifestyle factors as well as the examinations of the genetic basis of metabolism. We will measure the blood samples by Nightingale Health?s proprietary NMR metabolomics platform in Finland. The resulting metabolic biomarker measures will subsequently be analysed statistically for association with disease events (prevalence and incidence of all ICD-10 disease categories) and health factors using so-called phenome-wide association approaches covering subclinical disease markers, other blood biomarkers, life style and dietary data, as well as complete genomic information. We will request blood samples and participant data for the full cohort (~500,000 samples; 85 ul serum needed) and, if possible, also for one follow-up time point (~20,000 blood samples). The metabolomics measurements of the entire UK Biobank are expected to be completed within 18-24 months from sample arrival to Nightingale?s laboratory.
21 Publications
| Pub ID | Title | Author(s) | Year | Journal |
|---|
| 16683 | Adiposity, metabolites and endometrial cancer risk: inference from combinations of Mendelian randomization and observational analyses | Matthew A. Lee (+8) | 2025 | BMC Cancer |
| 9409 | Association of Stair Use With Risk of Major Chronic Diseases | Andrea Raisi (+8) | 2023 | American Journal of Preventive Medicine |
| 13281 | Association of circulating fatty acids with cardiovascular disease risk: analysis of individual-level data in three large prospective cohorts and updated meta-analysis | Fanchao Shi (+39) | 2024 | European Journal of Preventive Cardiology |
| 11040 | Atlas of plasma NMR biomarkers for health and disease in 118,461 individuals from the UK Biobank | Heli Julkunen (+15) | 2023 | Nature Communications |
| 17447 | Basal metabolic rate and risk for diabetes and its complications among 341,790 adults from the UK Biobank | Joseph Frimpong (+4) | 2026 | Diabetes Research and Clinical Practice |
| 7422 | Characterising metabolomic signatures of lipid-modifying therapies through drug target mendelian randomisation | Tom G. Richardson (+6) | 2022 | PLOS Biology |
| 17140 | Combined clinical, metabolomic, and polygenic scores for cardiovascular risk prediction | Scott C Ritchie (+15) | 2025 | European Heart Journal |
| 12314 | Effects of general and central adiposity on circulating lipoprotein, lipid, and metabolite levels in UK Biobank: A multivariable Mendelian randomization study | Joshua A. Bell (+12) | 2022 | The Lancet Regional Health - Europe |
| 15412 | Genome-wide analyses of variance in blood cell phenotypes provide new insights into complex trait biology and prediction | Ruidong Xiang (+8) | 2025 | Nature Communications |
| 12241 | Integrative analysis of metabolite GWAS illuminates the molecular basis of pleiotropy and genetic correlation | Courtney J Smith (+6) | 2022 | eLife |
| 11519 | Interplay of Metabolome and Gut Microbiome in Individuals With Major Depressive Disorder vs Control Individuals | Najaf Amin (+22) | 2023 | JAMA Psychiatry |
| 8720 | Life course plasma metabolomic signatures of genetic liability to Alzheimer's disease | Hannah Compton (+7) | 2024 | Scientific Reports |
| 9401 | Lipoprotein Characteristics and Incident Coronary Heart Disease: Prospective Cohort of Nearly 90 000 Individuals in UK Biobank | Danyao Jin (+5) | 2023 | Journal of the American Heart Association |
| 9408 | Low levels of small HDL particles predict but do not influence risk of sepsis | Fergus Hamilton (+4) | 2023 | Critical Care |
| 5390 | Metabolic biomarker profiling for identification of susceptibility to severe pneumonia and COVID-19 in the general population | Heli Julkunen (+3) | 2021 | eLife |
| 14309 | Metabolomic and genomic prediction of common diseases in 700,217 participants in three national biobanks | Jeffrey C. Barrett (+24) | 2024 | Nature Communications |
| 10232 | Predictive value of circulating NMR metabolic biomarkers for type 2 diabetes risk in the UK Biobank study | Fiona Bragg (+5) | 2022 | BMC Medicine |
| 7967 | Quality control and removal of technical variation of NMR metabolic biomarker data in ~120,000 UK Biobank participants | Scott C. Ritchie (+9) | 2023 | Scientific Data |
| 10326 | 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 | Maria Carolina Borges (+7) | 2022 | BMC Medicine |
| 8781 | The impact of reproductive factors on the metabolic profile of females from menarche to menopause | Gemma L. Clayton (+2) | 2024 | Nature Communications |
| 16264 | The relationship between polyunsaturated fatty acids and inflammation: evidence from cohort and Mendelian randomization analyses | Daisy C P Crick (+4) | 2025 | International Journal of Epidemiology |
