Longitudinal and genetic evaluation of type 2 diabetes and major depression
Lead Research Organisation:
UNIVERSITY OF EXETER
Department Name: Institute of Biomed & Clinical Science
Abstract
Depression and type 2 diabetes are growing health problems, with high costs to both individuals and society. Most research focuses on either depression or on type 2 diabetes. However, more people have both depression and type 2 diabetes than we would expect and therefore more research is needed to understand the complex relationship between these two conditions. At the moment there are many unanswered questions. For example, does having both depression and type 2 diabetes increase your risk of other adverse health outcomes (e.g. heart problems, leg ulcers etc.) further than having depression or type 2 diabetes alone?
Our research aims to use information from large studies with genetic data and primary health care records to test how: a) depression and type 2 diabetes are related to one another, b) risk factors (such as education and obesity) influence the depression and type 2 diabetes relationship, c) having both type 2 diabetes and depression impacts an individual's health, d) depression alters glucose levels for type 2 diabetics over time and e) the order and age of diagnoses alter outcomes.
To test our hypotheses, we will use two different but complementary approaches. Firstly, we will use genetics to allow us to infer causality, i.e. assess whether the relationships we see are real and not caused by 'noise' in the data. This is possible because our genetic code is fixed before birth and does not change as a result of our diet or lifestyle factors, such as smoking, which might otherwise lead to bias. Genes are therefore useful tools for testing the true causal link between two factors. For example, if there is a direct link from depression to type 2 diabetes, genes that increase the risk of depression will also have an effect on type 2 diabetes. Understanding the causal relationship is important from both a public health perspective, to ensure appropriate monitoring and treatment plans are in place and for patients. Secondly, we will use data from general practitioner (GP) records in over 200,000 patients with both type 2 diabetes and depression. This will allow us to answer several important questions. Firstly, we will test how depression alters blood glucose levels over time. All patients with type 2 diabetes are seen at the GP regularly (~ every 6 months) to have their glucose monitored. We will test if and how having depression as well as type 2 diabetes alters the changes in glucose levels over time and determine whether the relative timing of diagnosis (i.e. depression before type 2 diabetes or vice versa) is important. Secondly, we will focus on individuals with depression and test if having type 2 diabetes alters the progression of depression. For example, do individuals with both conditions have more depression episodes or are they more likely to develop more severe depression?
Our findings will be of crucial importance to individuals with both depression and type 2 diabetes. We will provide a step change in our understanding of this relationship and will work with clinicians and patients to ensure our findings are translated into appropriate public health messaging, which have the potential to improve treatment pathways and interventions for individuals with both type 2 diabetes and depression.
Our research aims to use information from large studies with genetic data and primary health care records to test how: a) depression and type 2 diabetes are related to one another, b) risk factors (such as education and obesity) influence the depression and type 2 diabetes relationship, c) having both type 2 diabetes and depression impacts an individual's health, d) depression alters glucose levels for type 2 diabetics over time and e) the order and age of diagnoses alter outcomes.
To test our hypotheses, we will use two different but complementary approaches. Firstly, we will use genetics to allow us to infer causality, i.e. assess whether the relationships we see are real and not caused by 'noise' in the data. This is possible because our genetic code is fixed before birth and does not change as a result of our diet or lifestyle factors, such as smoking, which might otherwise lead to bias. Genes are therefore useful tools for testing the true causal link between two factors. For example, if there is a direct link from depression to type 2 diabetes, genes that increase the risk of depression will also have an effect on type 2 diabetes. Understanding the causal relationship is important from both a public health perspective, to ensure appropriate monitoring and treatment plans are in place and for patients. Secondly, we will use data from general practitioner (GP) records in over 200,000 patients with both type 2 diabetes and depression. This will allow us to answer several important questions. Firstly, we will test how depression alters blood glucose levels over time. All patients with type 2 diabetes are seen at the GP regularly (~ every 6 months) to have their glucose monitored. We will test if and how having depression as well as type 2 diabetes alters the changes in glucose levels over time and determine whether the relative timing of diagnosis (i.e. depression before type 2 diabetes or vice versa) is important. Secondly, we will focus on individuals with depression and test if having type 2 diabetes alters the progression of depression. For example, do individuals with both conditions have more depression episodes or are they more likely to develop more severe depression?
Our findings will be of crucial importance to individuals with both depression and type 2 diabetes. We will provide a step change in our understanding of this relationship and will work with clinicians and patients to ensure our findings are translated into appropriate public health messaging, which have the potential to improve treatment pathways and interventions for individuals with both type 2 diabetes and depression.
Technical Summary
The prevalence of both type 2 diabetes and depression are increasing globally and previous research has demonstrated evidence that diagnosis with both conditions leads to poorer diabetes control and an increased likelihood of developing treatment resistant depression. However, the relationship between type 2 diabetes and depression is complex with many unanswered questions. The aim of our research is to use longitudinal health records and genetic analyses in 10,000s of individuals to establish a more complete understanding of the relationships between type 2 diabetes and depression. This project is important for several reasons; firstly, we will analyse genetic data in the UK Biobank to tease apart the causal relationships between diabetes and depression and improve our understanding of the consequences of both diabetes and depression; secondly we will use general practitioner health records in over 1 million type 2 diabetes patients to understand the temporal relationship between diabetes and depression. Our overall aim will be achieved by addressing related questions:
Is there a bidirectional causal relationship between depression and diabetes?
Does obesity and/or other modifiable risk factors mediate the relationship between depression and diabetes?
What are the consequences of having both depression and diabetes?
How does depression influence glycemic control in diabetes over time?
Does the timing of onset of depression relative to diabetes alter the relationship with glycemic control?
How does having type 2 diabetes alter the progression of depression across the lifecourse?
We will use genetic approaches, including Mendelian randomisation, and longitudinal statistical methods to address these questions.
This project will provide important information about the complex relationship between depression and diabetes, thereby informing global decisions on medical management and public health strategies for both conditions.
Is there a bidirectional causal relationship between depression and diabetes?
Does obesity and/or other modifiable risk factors mediate the relationship between depression and diabetes?
What are the consequences of having both depression and diabetes?
How does depression influence glycemic control in diabetes over time?
Does the timing of onset of depression relative to diabetes alter the relationship with glycemic control?
How does having type 2 diabetes alter the progression of depression across the lifecourse?
We will use genetic approaches, including Mendelian randomisation, and longitudinal statistical methods to address these questions.
This project will provide important information about the complex relationship between depression and diabetes, thereby informing global decisions on medical management and public health strategies for both conditions.
