Principal Investigator: Dr Briana Mezuk
University of Michigan, MI, USATags: 41812, depression, epidemiology, etiology, genetics/genotyping, sleep
Depression is a serious disorder that can cause mental distress, impair the ability to function in everyday life, and increase the risk for physical diseases like heart disease and diabetes. According to the World Health Organization, depression is the leading cause of disability worldwide. By studying the factors that contribute to this disease, we can help to come up with new ways to prevent and treat depression at a population level.
The goal of this project is to use genetic data from the UK biobank to test several theories about the causes of depression. Existing studies have found many factors that are associated with depression, but it is often hard to tell why these associations exist. Because a person’s genes stay the same throughout their life, studies using genetic data can help us to explore complicated questions about the causes of depression.
The first aim of this project will be to look at the relationship between certain signaling chemicals found in the blood and depression. Studies have previously found that high or low levels of these chemicals are associated with depression. However, many factors associated with depression can influence levels of these chemicals, including sleep and exercise. This aim will explore whether these chemicals are a true causal factor for depression, or whether this association is due to other factors such as health behaviors in people with depression.
The second aim of this project will be to look at the relationship between depression and sleep. We know that people with depression often have problems with their sleep, but we do not know why. This aim will look at whether there is overlap between the genes that are associated with depression and the genes that are associated with sleep problems
The third aim of this project will be to look at whether depression is a single disorder, or if it is multiple disorders that happen to have similar symptoms. Depression can only be diagnosed by using symptoms reported by the person who has it, but sometimes different diseases can cause similar symptoms. This aim will use genetic and symptom data from the UK biobank to look at whether there are useful ways to identify distinct subgroups of people with depression.
It is expected that this project will be completed over a two-year period.
Project extension – January 2020
The new scope keeps the same aim 1, but removes the original aim 2 and aim 3 and replaces them with the following:
Aim 2 will use genetically-related individuals in the UK Biobank sample to examine factors influencing reporting of family health history. In the absence of genetic data, and for conditions with multifactorial etiology such as depression, measurement of family history is an important element of risk stratification. However, many factors are likely to influence the accuracy of family history reporting, including gender, type of relationship, stigma associated with the health condition, and the reporting individual’s own health status and risk awareness. These factors are likely to introduce bias into studies relying on self-reported family history, and can be difficult to examine with conventional datasets. This aim will seek to quantify the sources of measurement error in family history reporting using related individuals in the UK Biobank (who have each reported on their family health history and their own health history) across several disorders, with a focus on depression. The primary questions will be examination of how accuracy of family history self-reporting compares across physical disorders and depression, and how the reporting individual’s own depression status might influence their reporting of depression in their family history. Examination of these questions can improve the ability to draw appropriate inferences in studies of depression that make use of such self-reported data.
Aim 3 will examine the nature of the relationship between depression and common medical conditions (diabetes, seasonal allergies, and asthma). Although depression commonly co-occurs with these medical conditions, the etiologic nature of these relationships is unclear. Studies of diseases which are commonly self-diagnosed (eg. seasonal allergies) may be more likely to suffer from bias due to differential self-diagnosis in individuals with depression. Examination of comorbidity can also be complicated in under-identified diseases such as diabetes where it is unclear whether it is the disease itself or an individual’s awareness of their disease status that should be evaluated as a potential cause of depression. Aim 3 will use multiple analyses, including stratified Mendelian Randomization and stratified comparison of polygenic risk scores to self-reported disease status, to examine how individuals’ awareness or assessment of their disease status influences the apparent relationships between diseases.
Last updated Jan 31, 2020