Neuroimaging biomarkers in Alzheimer’s disease

Abstract

Alzheimer’s disease (AD) is characterized by an accumulation of abnormal plaques and tangles in the brain, a process that is estimated to begin years before the appearance of clinical symptoms. Individuals with subjective memory decline (SMD) or mild cognitive impairment (MCI) run a higher risk of developing AD than cognitively normal (CN) people. The main aim of this thesis was to investigate the potential use of structural neuroimaging biomarkers in AD. A disease severity index (SI) based on multivariate data analysis of MRI-derived structural measures was generated. The SI was evaluated to discriminate AD patients from CN individuals as well as to monitor disease progression and predicting conversion to AD in SMD/MCI.

In study I, the use of structural imaging and cerebrospinal fluid measures and factors that may affect the use of these methods in dementia work-up were investigated. The results showed that 94% of the patients had a brain scan performed. The results highlighted the role of MRI as an extended dementia investigation tool in younger patients with less severe cognitive impairment and a clinical presentation of less clear dementia symptoms. In study II, the performance of the SI in discriminating AD patients from CN subjects and in predicting conversion from MCI to AD was investigated. The role of age correction was also investigated and how it affected classification/prediction. Age correction did not only effectively eliminate the effect of age, it also highlighted age associations in other factors such as APOE genotype, global cognitive impairment and gender. In study III, the SI was longitudinally evaluated for monitoring disease progression in subjects with MCI. The results showed the potential of the SI to identify MCI subjects at risk of converting to AD and that disease progression could be monitored in an accurate way. Further, using the SI it could be observed that APOE genotype and amyloid pathology may independently modulate disease-related brain structural changes. In study IV, the SI was validated in a group of healthy individuals with SMD from a different cohort. Using the SI, a subgroup of SMD subjects who manifested structural brain patterns similar to AD was identified. These subjects had lower cognitive performance, higher amyloid burden and worse clinical progression compared to SMD individuals with structural brain patterns similar to CN. The SI as a neuroimaging biomarker was studied in the whole disease continuum from CN and SMD to MCI and AD. The SI showed strong potential to be used as a sensitive tool for predicting and monitoring disease progression in clinical trials or clinical practice. Nevertheless, in future the SI should be validated in clinical cohorts and the relationship between the SI and factors such as genotype and other AD biomarkers should be further investigated.