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Approved Research

The impact of Ribosomal DNA (rDNA) copy number on birth weight and adult obesity

Principal Investigator: Professor Vardhman Rakyan
Approved Research ID: 83271
Approval date: April 21st 2022

Lay summary

There is a part of the human genome, called the ribosomal DNA (rDNA), that is important for making all proteins in the cell. It is present as hundreds of copies in the human genome and it is known that the number of copies of rDNA varies significantly amongst individuals. However, this variation in the rDNA is overlooked in all ongoing large-scale human genetic studies. Based on our preliminary human and mouse work, we think that rDNA copy number variation influences birth weight. Separately, we have evidence to suggest that rDNA copy number also has an influence on adult BMI, and we think that this is related to the birth weight effect. We would like to replicate and confirm our findings in a much bigger dataset i.e. the UK Biobank. The initial analyses will be complete well before the 36 months deadline. If we can replicate our initial findings using the UK Biobank data, it will represent a novel example of human genetic variation that influences important phenotypes, but has never been considered previously in powerful large-scale analyses.


Q1. Is there a positive association between rDNA copy number and birth weight?

Q2. Is there an inverse association between rDNA copy number and current BMI?

The original aim of the project was to determine if rDNA copy number represents a novel genetic association with birth weight. The secondary aim is to ask if this initial association impacts BMI in adult life.


Now, based on our initial analysis, we think that rDNA copy number could associate with other human phenotypes. For this reason, we would like to perform a wider ranging investigation that looks at all the phenotypes available in the UK Biobank. This is a similar approach taken by Mukamael et al. 2021 who analysed protein-altering VNTRs in 415,280 UK Biobank participants for association with 786 phenotypes, identifying some of the strongest associations of common variants with human phenotypes, including height, hair morphology, and biomarkers of health. We would like to do something similar but for rDNA copy number instead.