New perspectives on familial clustering of Alzheimer's disease: the role of rare genetic risk variants.

Alzheimer's disease (AD) is an important threat to both personal and publich health. Familial clustering of AD has long been known, and in the past few decades, important progress has been made in unraveling the genetics of AD. For patients and their relatives today, the most tangible benefit of this progress is the ability to genetically diagnose or predict the disease. Nevertheless, this only applies to a minority of families, in which a mutation in APP, PSEN1 or PSEN2 has been identified that causes a rare autosomal dominant form of AD. For the majority of patients, the disease has a complex genetic background, which cannot be readily translated into accurate risk prediction. Remarkable in this light is our recent observation that rare predicted loss-of-function mutations in the AD risk gene ABCA7 are associated with autosomal dominant pattern of inheritance of AD. Multiplex AD families segregating such rare variants represent a distinct subgroup in which some of the benefits of genetic testing may hold true.The key aim of this PhD project is to get a better understanding of the role of these rare risk variants in familial clustering of AD, with the ultimate goal to assess if and how the knowledge of carrier status of such a variant can be used in genetic risk prediction. A variety of state-of-the-art approaches will be used to address this aim. Molecular characterization of rare variants through RNA sequencing analysis of lymphoblast cell lines and brain will contribute to a better understanding of the impact of the mutations, as well as a delineation of neutral and pathogenic variants. Genetic-epidemiological characterization through DNA sequencing on additional cohorts will shed further light on the frequency and penetrance of these mutations. The mode of action and causes of phenotypic heterogeneity will be investigated in derivatives of induced pluripotent stem cells of mutation carriers. Finally, this patient-derived model will be used to investigate the potential of compounds to modify the effect of the mutation, eventually enabling targeted treatment.This PhD project covers an uncharted but promising territory in the battle against AD, particularly considering the increasing focus in this battle on patient stratification, early detection and precision medicine.

Keywords:ALZHEIMER'S DISEASE, GENETIC RISK

Disciplines:Genetics, Systems biology, Molecular and cell biology, Neurosciences, Public health care, Public health sciences, Public health services, Biological and physiological psychology, Cognitive science and intelligent systems, Developmental psychology and ageing