Is depression a modifiable risk factor for Alzheimer's disease?
- PI
- Sinclair, Lindsey
- DAR ID
- 11238
- Initial Approval Date
- September 17, 2024
- Current DAR Status
- Closed
- PI Institution
- University of Bristol
- PI Institution Country
- United Kingdom
- PI Institution Type
- Non-Profit
Requested Datasets (15)
NG00022ADC1 - Alzheimer's Disease Center Dataset 1NG00023ADC2 - Alzheimer's Disease Center Dataset 2NG00024ADC3 - Alzheimer's Disease Center Dataset 3NG00068ADC4 - Alzheimer's Disease Center Dataset 4NG00069ADC5 - Alzheimer's Disease Center Dataset 5NG00070ADC6 - Alzheimer's Disease Center Dataset 6NG00071ADC7 - Alzheimer's Disease Center Dataset 7NG00136ADC8 - Alzheimer's Disease Center Dataset 8NG00137ADC9 - Alzheimer's Disease Center Dataset 9NG00138ADC10 - Alzheimer's Disease Center Dataset 10NG00139ADC11 - Alzheimer's Disease Center Dataset 11NG00140ADC12 - Alzheimer's Disease Center Dataset 12
Research Use Statement
Objectives
I aim to identify whether individuals with normal cognition and a high genetic risk of depression are at higher risk of developing atrophy in brain regions affected by Alzheimer’s disease than those at lower genetic risk.
Study Design
Depression was identified by the Lancet commission in 2017 as a potentially modifiable risk factor for Alzheimer’s disease. The extent to which this risk is actually modifiable is unknown, as are the mechanisms by which depression increases dementia risk. We wish to use polygenic risk scores (PRS) to look at whether someone’s total genetic risk for depression makes them more likely to have shrinkage of brain regions affected in AD and/or involved in mood over time. If individuals at higher genetic risk of depression have greater shrinkage of brain regions affected early in AD e.g. medial temporal lobe, this could help to explain part of the increase in risk. We will do this using NACC and ROSMAP data on people with normal cognition at the time that their MRI scans were performed.
We will use logistic regression and mediation analyses to examine whether social contact may mediate some of the increased risk for dementia in those who are depressed. We would like to be able to include genetic risk for depression and AD in this analysis.
Analysis Plan
I will use data from individuals in NACC and ROSMAP with normal cognition at the time of their MRI. I will examine whether the PRS is related to the risk of AD by comparing mean regional brain volumes for those in the highest and lowest quartile of PRS-D. Included individuals will need to have completed ≥1 depression rating scales and ≥1 MRI. In NACC depression will be defined as GDS ≥8 and/or NPI-depression severity ≥2 & distress ≥3. In ROSMAP depression will be determined using DSM-IV diagnoses & CESD ≥4. The PRS for depression will be calculated using R or PLINK using data from the most recent depression GWAS. I plan to use lassosum2, ldpred2 and PRS clumping & thresholding and to include a smaller GWAS with better phenotyping (Wray et al 2018) in a secondary analysis. The PRS for AD will also be calculated and included as a co-variate in analyses
I aim to identify whether individuals with normal cognition and a high genetic risk of depression are at higher risk of developing atrophy in brain regions affected by Alzheimer’s disease than those at lower genetic risk.
Study Design
Depression was identified by the Lancet commission in 2017 as a potentially modifiable risk factor for Alzheimer’s disease. The extent to which this risk is actually modifiable is unknown, as are the mechanisms by which depression increases dementia risk. We wish to use polygenic risk scores (PRS) to look at whether someone’s total genetic risk for depression makes them more likely to have shrinkage of brain regions affected in AD and/or involved in mood over time. If individuals at higher genetic risk of depression have greater shrinkage of brain regions affected early in AD e.g. medial temporal lobe, this could help to explain part of the increase in risk. We will do this using NACC and ROSMAP data on people with normal cognition at the time that their MRI scans were performed.
We will use logistic regression and mediation analyses to examine whether social contact may mediate some of the increased risk for dementia in those who are depressed. We would like to be able to include genetic risk for depression and AD in this analysis.
Analysis Plan
I will use data from individuals in NACC and ROSMAP with normal cognition at the time of their MRI. I will examine whether the PRS is related to the risk of AD by comparing mean regional brain volumes for those in the highest and lowest quartile of PRS-D. Included individuals will need to have completed ≥1 depression rating scales and ≥1 MRI. In NACC depression will be defined as GDS ≥8 and/or NPI-depression severity ≥2 & distress ≥3. In ROSMAP depression will be determined using DSM-IV diagnoses & CESD ≥4. The PRS for depression will be calculated using R or PLINK using data from the most recent depression GWAS. I plan to use lassosum2, ldpred2 and PRS clumping & thresholding and to include a smaller GWAS with better phenotyping (Wray et al 2018) in a secondary analysis. The PRS for AD will also be calculated and included as a co-variate in analyses
Non-Technical Summary
The development of depression in mid to later life increases a person's risk of developing Alzheimer's disease. Although depression can be treated, at the moment it is not clear if this treatment may also prevent AD later in life. It is therefore important to know how depression itself increases this risk.
We aim to find out
1. What changes in the brains of people who are depressed?
2. Could these changes increase dementia risk?
Methods
1. We will use existing data for brain tissue from individuals without dementia. We will use this to find out which pathways differ in people with depression. We will study both areas involved in mood and areas affected early in AD.
2. We will examine whether genetic risk of depression is linked to brain shrinkage.
3. We will assess the relationship between depression and loneliness/social isolation and whether social isolation may be a mechanism by which depression increases risk.
We aim to find out
1. What changes in the brains of people who are depressed?
2. Could these changes increase dementia risk?
Methods
1. We will use existing data for brain tissue from individuals without dementia. We will use this to find out which pathways differ in people with depression. We will study both areas involved in mood and areas affected early in AD.
2. We will examine whether genetic risk of depression is linked to brain shrinkage.
3. We will assess the relationship between depression and loneliness/social isolation and whether social isolation may be a mechanism by which depression increases risk.
Reported Publications
Publications shown are those reported by investigators through NIAGADS DAR reporting and renewal processes and may not represent a complete list of publications associated with the project.
No publications have been reported for this DAR.