| Title: | Estimation and implications of the genetic architecture of fasting and non-fasting blood glucose |
| Journal: | Nature Communications |
| Published: | 27 Jan 2023 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/36707517/ |
| DOI: | https://doi.org/10.1038/s41467-023-36013-1 |
| URL: | https://www.nature.com/articles/s41467-023-36013-1.pdf |
Publication 11016
WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
Abstract
The genetic regulation of post-prandial glucose levels is poorly understood. Here, we characterise the genetic architecture of blood glucose variably measured within 0 and 24 h of fasting in 368,000 European ancestry participants of the UK Biobank. We found a near-linear increase in the heritability of non-fasting glucose levels over time, which plateaus to its fasting state value after 5 h post meal (h2 = 11%; standard error: 1%). The genetic correlation between different fasting times is > 0.77, suggesting that the genetic control of glucose is largely constant across fasting durations. Accounting for heritability differences between fasting times leads to a ~16% improvement in the discovery of genetic variants associated with glucose. Newly detected variants improve the prediction of fasting glucose and type 2 diabetes in independent samples. Finally, we meta-analysed summary statistics from genome-wide association studies of random and fasting glucose (N = 518,615) and identified 156 independent SNPs explaining 3% of fasting glucose variance. Altogether, our study demonstrates the utility of random glucose measures to improve the discovery of genetic variants associated with glucose homeostasis, even in fasting conditions.</p>
10 Authors
- Zhen Qiao
- Julia Sidorenko
- Joana A. Revez
- Angli Xue
- Xueling Lu
- Katri Pärna
- Harold Snieder
- Peter M. Visscher
- Naomi R. Wray
- Loic Yengo
1 Application
| Application ID | Title |
|---|---|
| 12505 | Dissecting the genetic basis of relationships between early-life and later-life events |
Enabling scientific discoveries that improve human health