Scientific rationale: Several neurodegenerative diseases are known to share certain symptoms and biological pathways. A better understanding of similarities and dissimilarities among these diseases could provide important insight into the biological mechanism leading to onset and progress of neurodegeneration. Investigation of genetics in different worldwide populations may further help us to discover the contributing genes and thereby dissect the biological pathways. To date, dozens of different regions of human genome or genetic loci have been discovered for various neurodegenerative disorders, predominantly in individual of Causcasian ancestry. However, our knowledge on generalization of the genetic findings to other ethnic groups remains limited. In addition, existence of genomic regions known to be influence various biological processes makes interpretation of significant causal findings extremely complex.
Aim: The present project aims to replicate the association of genetic loci observed for neurodegenerative disorders including Alzheimer’s disease, Parkinson’s disease, age-related macular degeneration, amyotrophic lateral sclerosis and multiple sclerosis in previously reported European datasets in the UK Biobank (UKB) dataset. The project further aims to merge different worldwide datasets to discover novel genomic regions. Additionally, the dataset will be used to conduct polygenic risk score generation which summarizes effect of associated genetic loci in every individual. And lastly, we aim to dissect causal pathways underlying neurodegenerative disorders by using the modern statistical approach of Mendelian Randomization (MR) which uses genetic loci as proxies of various risk factors for judging association with respective neurodegenerative disorders.
Project duration: The duration of the project will be three years, from 2020-2023.
Public health impact: We expect to discover genetic variants associated with onset and progress of neurodegeneration. The genetic variants will further help to identify the underlying causal bio-markers. The findings could provide suggestions for novel drug targets and disease management.