Submitted by aml95 on Tue, 29/04/2025 - 14:25
A study led by Dr Alexander Mörseburg* and colleagues at the IMS-MRL and MRC Epidemiology Unit in Cambridge, has used an “ageing clock” with UK Biobank data from 44,435 to show that people with type 2 diabetes and higher BMI were more likely to have a biological age older than their chronological age.
As we age, levels of different proteins in our body change. In some cases, this is due to diseases that are more common in old age, in others it reflects general processes of ageing.
Published in the journal npj Aging, this study involved two analyses. In the first, the researchers were able to generate an ageing clock based on a panel of approximately 1,500 proteins. This clock was associated with age-related diseases and with all-cause mortality. They also demonstrated that this protein clock was correlated with other biological measures of human aging such as telomere length and patterns of methylation.
In the second analysis, they identified three regions of the genome where variation was linked to their measure of accelerated biological aging. One of these was close to BRCA1 - a well-established breast cancer gene. However, the signal was distinct from the variant that causes cancer. Another region, near to TET2 is known to play an important role in methylation, one of the other physiological measures of biological aging used widely. After finding the effects in the genome, the team were able to use the genetic data to show that higher levels of BMI and a diagnosis of type 2 diabetes were both associated with faster biological ageing. This reinforces the idea that metabolic disease can have wide-spread physiological effects.
This study demonstrates how much of a “whole-body" disease type 2 diabetes is. It has a detectable impact which increases the levels of proteins that we associate with old age. Furthermore, it is hoped that the protein clock developed can be used as a biomarker for the effectiveness of preventative interventions and for drug development.
Reference: Mörseburg, A., Zhao, Y., Kentistou, K.A. et al. Genetic determinants of proteomic aging. npj Aging 11, 30 (2025). https://doi.org/10.1038/s41514-025-00205-4
* Alexander Mörseburg is now a Research Associate in population multi-omics at the Cambridge Cardiovascular Epidemiology Unit
Image by xaviandrew from Pixabay
