Approved Research

Elucidating the genetic basis of both normal and abnormal brain structure

Lay summary

Age-associated disorders of the brain, like dementia and Parkinson's disease, currently affect more than 50 million people worldwide. Moreover, due to population aging, the overall prevalence of these disorders is expected to rise dramatically in the coming years, almost tripling by 2050 according to the World Health Organization. Yet, there are still no treatments available that could slow down the relentlessly progressive course of these debilitating brain disorders. To facilitate the development of new treatments for these age-associated brain disorders, it is important to get a better understanding of the genetic factors that contribute to differences in both normal and abnormal brain structure among different individuals. This is because identification of these genetic factors will enable a better understanding of the factors that play a role in the pathogenesis of these brain disorders and thus could be targeted by new drugs and therapies.

We have recently developed a number of computer algorithms that, using artificial intelligence, can automatically estimate the sizes of different brain structures and lesions based on brain imaging data. Importantly, our algorithm can estimate the sizes of different brain structures that until recently were very difficult to automatically evaluate; these regions include the olfactory bulb (a region important for regulating the sense of smell), the hypothalamus (a region important for regulating a range of bodily functions like sleep, body weight, mood and memory) and the cerebellum (a structure that controls both voluntary and involuntary movements). In this research project, we will first apply these new computer algorithms to brain imaging data collected as part of the UK Biobank. Second, using genetic data collected from the participants of the UK Biobank study, we will identify the genetic variants that are related to differences in these brain structures. And finally, using bioinformatic analyses, we will search for molecular mechanisms that could account for how these genetic variants lead to differences in brain structure.

During the course of three years, this research project is expected to yield several novel insights into the genetic factors that determine both normal and abnormal brain structure. In turn, these insights will be of vital importance for the development of novel therapies for the treatment of a range of debilitating brain disorders that currently afflict millions of people globally and for which still no effective disease-modifying therapies exist.