PhD defence V. (Vikram) Venkatraghavan

Neurodegenerative diseases such as Alzheimer's disease are notoriously heterogeneous; pathologically as well as in their clinical presentation in patients. There are differences between patients in terms of the pathways of progression, the speed of progression, and the effect the progression has on the patient's cognition. This myriad of differences not only makes clinical diagnosis very challenging, but also has major implications for the efficacy of drug trials. As heterogeneous as these diseases are, there is an underlying order in their progression. An underlying method to their disruption of homeostasis. An underlying symphony leading to the cacophony.

This thesis describes the development of novel data-driven methods for understanding the orderly progression of neurodegenerative diseases, and validates their utility in providing insights into the progression patterns of four such diseases: Alzheimer's disease (AD), frontotemporal dementia (FTD), Creutzfeldt-Jakob disease (CJD) and multiple sclerosis (MS). The thesis further validates the diagnostic and prognostic utilities of the methods, their generalizability from research cohorts to clinical cohorts, as well as their ability to identify preclinical and prodromal stages in a population-based cohort. The insights into disease progression pathways obtained using these methods, at a group level as well as for each patient, could be invaluable for targeted interventions and drug trials in the future.

Due to corona, the PhD defences do not take place publicly in the usual way in the Senate Hall or in the Professor Andries Querido Room. The candidates will defend their dissertation either in a small group or online.