Early identification of Alzheimer's disease: dynamic biomarkers for enrichment of trials

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Alzheimer's disease (AD) is a fatal disease which in the UK alone directly affects 820,000 people, costing the UK economy £23 billion pounds, more than cancer and heart disease combined. All current treatments for Alzheimer's disease (AD) only provide relief from symptoms, despite many attempts to develop a cure. Recent research has shown that brain scans can be used to spot early signs of AD, up to 20 years before a clinical diagnosis. Researchers are now racing to develop drugs that can delay the onset of AD, based on the belief that it will be easier to delay rather than reverse the disease process. The major barrier in the development of such a treatment is the expensive brain scans necessary to identify people with early signs of AD. This fellowship will develop a relatively inexpensive alternative to make it practical to identify large numbers of people with the early signs of AD, in whom drugs to delay AD onset will be tested.Within the fellowship Dr. Steven Kiddle will need to apply and develop statistical approaches to integrate complex data from brain scans, genetics, functional genomics and cognitive tests. He will be mentored by an expert in biostatistics, Dr. Chris Wallace from Cambridge University, and will collaborate with clinically trained researchers Professor Simon Lovestone and Dr. Claire Steves. Past research by Dr. Steven Kiddle and others have identified blood proteins which could be measured in a blood test, this could identify early signs of AD as an alternative to expensive brain scans. However, these early findings need much further validation before being used in the clinic. During this fellowship Dr. Kiddle will examine the potential of these blood proteins, as well as genetics and scores from cognitive tests, to identify subjects with early signs of AD.This work will begin with a study in twins to determine which blood protein levels are affected by their current health, controlling for genetics. This will include a study that uses both blood tests and brain scans in identical twins, to see if the proposed blood test can reveal differences in early signs of AD in genetically identical individuals. Further work will attempt to identify early signs of AD using cognitive tests, by adapting existing assessments of cognitive abilities. Cognitive tests consist of a set of individual tasks which test different aspects of memory and cognition. Total scores for existing cognitive tests are known to be sensitive to late AD, but are thought to be less sensitive to early stage AD. However, individual tasks, or a clever combination of tasks, have not yet been assessed for ability to identify people in the early stages of AD. In addition, the combination of genetic, cognitive and blood markers may allow subjects to be identified with greater accuracy than each marker alone.For blood markers to reflect signs of AD in the brain they must pass the blood-brain barrier. To investigate this I will study post-mortem brains from people who had been diagnosed with AD in life, and an equal number of people who had not recieved an AD diagnosis. Integrative analysis will be performed to link data on neuropathology, genetics, and multiple genomic levels, such as: epigenetics (which regulates gene expression), gene expression and protein levels. Dr. Kiddle will collaborate with Dr. Chris Wallace at Cambridge University to further develop statistical approaches tailored to this approach.Finally, Dr. Kiddle will use statistical models to study causal relationships between early signs of AD and the best genetic, blood protein and cognitive markers. This novel approach will reveal which blood protein and cognitive markers dynamically reflect the early signs of AD, and therefore will reveal which markers should be studied in the future. Funding will be sought to setup large-scale studies to assess the utility of these markers.