There are many active research projects accessing and applying shared ADNI data. Use the search above to find specific research focuses on the active ADNI investigations. This information is requested annually as a requirement for data access.
| Principal Investigator | |
| Principal Investigator's Name: | Lindsey Sinclair |
| Institution: | University of Bristol |
| Department: | Dementia Research Group |
| Country: | |
| Proposed Analysis: | Background Up to 16% of individuals with Alzheimer's Disease (AD) develop depression during their illness.(Asmer et al., 2018) Depression in dementia is difficult to treat and currently available anti-depressants have been shown not to work in individuals with AD. (Orgeta, Tabet, Nilforooshan, & Howard, 2017) The underlying biology of depression in AD is not known. Some, but not all research, has suggested that it may have a vascular component (e.g. (Anor et al., 2017; Asmer et al., 2018; Lee et al., 2015)). Depression occurring during AD is distressing for the patient and may increase carer burden. (Sousa et al., 2016) There is a clear need for new approaches. It was first shown 30 years ago that a family history of depression increases the risk of an individual developing depression during AD, but the underlying biology remains unclear. (Pearlson et al., 1990; Strauss & Ogrocki, 1996) Depression is a common mental illness affecting 13% of the population during their lives.(Takayanagi et al., 2014) Alzheimer’s disease (AD) is the most common form of late-life dementia. Its incidence is set nearly to triple by 2050, due to the ageing of the population.(Alzheimer's Association ) As with all dementias it has a devastating effect on patients and those around them. Unfortunately depression affects nearly 1 in 5 of those who suffer from Alzheimer’s Disease. (Asmer et al., 2018) It seems to peak early in the disease process with a second peak later in the illness.(Vik-Mo, Giil, Ballard, & Aarsland, 2018) It can be a very challenging diagnosis to make later in the illness when the patient is less able to communicate. Depression occurring during AD is distressing for the patient and may increase carer burden. (Sousa et al., 2016) Equally unfortunately existing drug treatments for depression do not help individuals with depression in Alzheimer’s disease. (Orgeta et al., 2017) Efforts are being made to adapt psychological therapies to help with patient group, for example the ongoing UK based PATHFINDER trial. The underlying biology of depression in AD is poorly understood. It remains unclear whether it is a consequence of the AD process or an unrelated co-morbid illness. In the last 30 years much effort has gone into studying many potential biomarkers e.g cortical thinning, amyloid, 5-HT and noradrenaline.(Holmes, Arranz, Collier, Powell, & Lovestone, 2003; Lebedeva et al., 2014; Perin et al., 2018; Zubenko, 2005) The results have been conflicting and new approaches are required. Proposed Analyses I propose to use ADNI data to examine which brains areas have reduced perfusion and/or increased atrophy in individuals who become depressed (geriatric depression scale score ≥8) during the course of their AD. Brain Atrophy I will use existing MRI data on longitudinal atrophy rates to examine whether individuals with depression during AD have greater atrophy on serial MRIs than individuals with AD who did not become depressed. I will use a region of interest analysis to examine atrophy in areas of the brain known to be associated with low mood. These areas will include the orbitofrontal cortex, dorsolateral prefrontal cortex, anterior cingulate, precuneus, amygdala, other components of the limbic system and the periaqueductal gray. Correction for multiple testing will be applied, where appropriate to do so. Assuming an SD of 330mm3 and an alpha of 0.05, a sample size of 50 in each group would give 80% power to detect a between group difference of 200 mm3 on MRI.(Teipel et al 2018). White Matter Hyperintensities I will use existing data within ADNI on white matter hyperintensities seen on MRI to examine whether these occur more frequently in individuals with depression during AD. Perfusion I will use FDG-PET data to examine whether individuals with depression during AD have evidence of greater hypoperfusion than individuals without depression during their AD. Again I will use a region of interest analysis on brain areas known to be associated with low mood. I propose to use the existing Berkley FDG-PET variables available within ADNI. |
| Additional Investigators | |
| Investigator's Name: | Seth Love |
| Proposed Analysis: | Professor Love will guide the analyses mentioned previously. |
| Investigator's Name: | Clive Ballard |
| Proposed Analysis: | Professor Ballard will guide the analyses mentioned previously. |
| Investigator's Name: | Peter Henley |
| Proposed Analysis: | PhD student. He will look at how the different neuropsychiatric symptoms in dementia relate to each other using principal component analysis. He then also plans to look at genetic correlations with these sets of symptoms. |
