B4033 - The study of rare variants and their longitudinal effects on metabolic and anthropometric traits 28-02-2022 - 100918 - 11/04/2022

B number: 
Principal applicant name: 
Brian Lam | IMS-MRL, University of Cambridge (United Kingdom)
Prof Stephen O'Rahilly, Dr Sam Lockhart, Dr Giles Yeo
Title of project: 
The study of rare variants and their longitudinal effects on metabolic and anthropometric traits (28-02-2022 - 10:09:18)
Proposal summary: 

We know that some people carry rare mutations that disrupt the normal function of critical metabolic pathways, leading to conditions such as obesity and/or diabetes. Genome sequencing studies are increasingly identifying such rare mutations. Using knowledge about the precise structure and function of the proteins encoded by these genes, as well as experimental data generated in the lab, we can determine which rare variants are likely to be disruptive.

After identifying mutations that disrupt protein function, we can use the wealth of data available in ALSPAC to determine how possessing a disrupted protein affects a persons growth and metabolism. This will allows us to infer the function of proteins in human physiology, and will identify new drug targets for metabolic diseases like obesity and diabetes.

Impact of research: 
- New information relating to the function of specific genes in human biology - Ultimately, we envision this work will discover novel regulators of human metabolism and identify viable targets for drug development in cardiometabolic diseases.
Date proposal received: 
Tuesday, 29 March, 2022
Date proposal approved: 
Monday, 4 April, 2022
Endocrinology, Diabetes, Eating disorders - anorexia, bulimia, Fertility/infertility, Gastrointestinal, Hypertension, Obesity, Pregnancy - e.g. reproductive health, postnatal depression, birth outcomes, etc., Cell culture, DNA sequencing, Statistical methods, GWAS, Mass spectrometry, Medical imaging, Metabolomics, Microarrays, NMR, Proteomics, RNA, Biological samples -e.g. blood, cell lines, saliva, etc., Biomarkers - e.g. cotinine, fatty acids, haemoglobin, etc., Hormones - cortisol, IGF, thyroid, Liver function, Metabolic - metabolism, Nutrition - breast feeding, diet, Puberty, Sex differences, Statistical methods, Whole genome sequencing, BMI, Bones (and joints), Development, Genetic epidemiology, Genetics, Genomics, Genome wide association study, Growth