| Application: | 9310, Associations of blood biomarkers with cardiovascular disease and related cardiometabolic outcomes and risk prediction in the clinical setting |
| Title: | Glomerular filtration rate by differing measures, albuminuria and prediction of cardiovascular disease, mortality and end-stage kidney disease |
| Size: | 622992 B |
| Archived: | 9 Jul 2021 |
| Stability: | Complete |
| Personal: | No individual-level data |
Return 3638
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Notes
Chronic kidney disease is common in the general population and associated with excess cardiovascular disease (CVD), but kidney function does not feature in current CVD risk-prediction models. We tested three formulae for estimated glomerular filtration rate (eGFR) to determine which was the most clinically informative for predicting CVD and mortality. Using data from 440,526 participants from UK Biobank, eGFR was calculated using serum creatinine, cystatin C (eGFRcys) and creatinine-cystatin C. Associations of each eGFR with CVD outcome and mortality were compared using Cox models and adjusting for atherosclerotic risk factors (per relevant risk scores), and the predictive utility was determined by the C-statistic and categorical net reclassification index. We show that eGFRcys is most strongly associated with CVD and mortality, and, along with albuminuria, adds predictive discrimination to current CVD risk scores, whilst traditional creatinine-based measures are weakly associated with risk. Clinicians should consider measuring eGFRcys as part of cardiovascular risk assessment.Application 9310
Associations of blood biomarkers with cardiovascular disease and related cardiometabolic outcomes and risk prediction in the clinical setting
In UK Biobank planned blood tests are important in helping detect early signs of groups of related diseases in the heart, blood vessels, brain, as well as early signs of diabetes. We will investigate to what extent these blood tests tell us about how likely someone is to develop these conditions, how these conditions develop, and whether we can intervene. For instance, adding information from these tests might improve our ability to predict the risk of a person having a heart attack. By harnessing the power of genes, we will test whether some of these new markers cause disease. This project will aim to assess avenues to improve health care throughout the population by investigating the improvement of CVD risk scores. More sensitive CVD and related risk scores may lead to better targeting of treatment and a reduction in the burden of CVD in the population. Biomarker measurement in UK biobank has been commenced, and the first tranche of biomarkers to be measured are now known. We will assess whether these markers are associated with, and predict, risk of cardiovascular and metabolic-related conditions. Biomarkers of interest include: Lipids and lipoproteins (different measures of blood cholesterol), markers of inflammation, markers, of liver function, markers of renal function, sex hormones, markers of glucose control, and markers of bone health. Each of these has plausible biological mechanisms linking them to risk of cardiovascular and metabolic diseases. The full cohort with available data will be explored to maximise generalisability to the whole adult population.
| Lead investigator: | Professor Naveed Sattar |
| Lead institution: | University of Glasgow |
4 related Returns
| Return ID | App ID | Description | Archive Date |
|---|---|---|---|
| 2617 | 9310 | Association of Total and Differential Leukocyte Counts With Cardiovascular Disease and Mortality in the UK Biobank | 28 Oct 2020 |
| 2845 | 9310 | Comparison of Conventional Lipoprotein Tests and Apolipoproteins in the Prediction of Cardiovascular Disease | 23 Nov 2020 |
| 3671 | 9310 | Glycated Hemoglobin, Prediabetes, and the Links to Cardiovascular Disease: Data From UK Biobank | 27 Jul 2021 |
| 2844 | 9310 | Urinary Sodium Excretion, Blood Pressure, and Risk of Future Cardiovascular Disease and Mortality in Subjects Without Prior Cardiovascular Disease | 23 Nov 2020 |
1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 3639 | Glomerular filtration rate by differing measures, albuminuria and prediction of cardiovascular disease, mortality and end-stage kidney disease | Jennifer S. Lees (+13) | 2019 | Nature Medicine |
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