Background
Alzheimer’s disease is the most prevalent forms of dementia in elderly people characterised by cognitive impairment and loss of memory, affecting the quality of life. Unfortunately, there is no cure for Alzheimer’s disease yet, therefore, identifying risk factors and the molecular factors that underlie increased susceptibility to Alzheimer’s disease, will help early diagnose risk individuals to offer preventive care. Burgeoning evidence, particularly from animal and human studies, is pointing towards an intricate comorbid association between sleep disorder, particularly obstructive sleep apnea (OSA)-most prevalent forms of disorder in mid to elderly people. In this project, we aim to establish whether OSA has any causal association with risk of Alzheimer’s disease leveraging genome-wide association studies (GWAS). Next, the project will also seek to discover molecular factors i.e., gene regulation that underlie this relation between Alzheimer’s disease and OSA via integrating GWAS with molecular quantitative trait loci (QTLs) datasets. This will be an ideal project for a motivated and enthusiastic Honours student to study role of OSA (if any) on the risk of Alzheimer’s disease and molecular factors that underlie this association.
Approach
We will offer hands-on training to students on various methods, particularly, analysis of GWAS and molecular QTLs datasets, required for successful completion of this project. Students will be highly skilled and efficient on handling large-scale genomics datasets and analysis of such datasets using bioinformatics and statistical genetics methods.
Outcome
The anticipated outcomes of this project are to assess whether sleep disorders contribute to induce or accelerate the risk of Alzheimer's disease and identify molecular factor that could serve as potential biomarkers for this association. The findings from this study are expected to provide new insights into the genetic relationships between sleep disorders and Alzheimer’s disease. The student will gain valuable computational and analytical skills by applying bioinformatics and statistical genetics methods.
Required Skills or Experience
- Possess a basic understanding of genetics, molecular biology and bioinformatics.
- Have a keen interest in neurogenetics and familiarity with R programming language will be advantageous but not necessary.