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Approved research

Hormone processing in health and disease

Principal Investigator: Dr Elisa Araldi
Approved Research ID: 48008
Approval date: June 18th 2019

Lay summary

Physiological process such as energy balance, reproduction, regulation of body fluids, and growth, require tight hormonal balance, which is fundamental to prevent disease development and negative pathological outcomes. Therefore it is critical to identify genetic causes of hormone imbalance to monitor individuals at risk. By using data from the UK Biobank and applying epidemiological and molecular epidemiological methods, we aim to provide knowledge on the predisposition to endocrine disorders associated with hormone processing, focusing especially in patients that carry mutations on and around genes responsible for producing hormones. We will require genetic data, physical, clinical and biochemical information of patients, and we will correlate these data with mutations of hormone processing genes, to understand the genetic predisposition of developing hormone imbalance and endocrine disorders. The research will be conducted using standard statistical methods for the association between genetic variations measured as single nucleotide polymorphism (SNPs), and other variables related to endocrine regulation and endocrine disorders. The project will last 12 months, and the data will be validated with studies in animal models and in vitro. The results obtained from this study may in the future lead to better identification of patients at risk of endocrine disorders and ultimately prevention.

Scope extension:

Several GWAS studies have shown that missense mutations in the enzyme peptidylglycine alpha-amidating monoxygenase (PAM) are associated with type 2 diabetes. The aim of this study is to infer from genetic and clinical data of patients carrying the mutations, how PAM contributes to diabetes development and progression. Furthermore, many hormones essential for proper physiological functions are amidated, therefore SNPs that modulate the expression of PAM might also affect other endocrine tissues and physiological functions. By correlating individual genetic and clinical data we will be able to demonstrate what is the contribution of PAM in normal physiology and in disease.

Therefore the aims of this project are:

1) Correlate clinical, biochemical and genetic data of individuals carrying the PAM mutations to understand the etiology of PAM-induced type 2 diabetes;

2) Understand the role of PAM in thyroid function, growth, fluid homeostasis, energy balance, sleep, through the study of SNPs around the PAM locus and correlations with population's data.

New scope:

3) Understand how PAM and PAM-mediated physiological function affects lifespan