Genetic variation in mineral-transport genes may alter mineral homeostasis and impact different disease outcomes and phenotypic traits. Common polymorphisms or single nucleotide polymorphisms (SNPs) account for only a portion of disease and phenotypic trait heritability. Therefore, analyses of rare variants (minor allele frequency < 1%) have the potential to explore the full scope of genetic heritability to disease risk and trait variability.
Exome sequencing data available in the UK Biobank will be used to extract rare polymorphisms in mineral metabolism genes. Rare variants will be annotated using Variant Effect Prediction (VEP) software to separate loss-of-function or damaging coding/missense mutations from benign variants.
Aim1: To develop a bioinformatic software pipeline to identify rare, deleterious mutations in mineral transporter genes.
Aim 2: To study the associations of rare coding mutations and common polymorphisms in mineral metabolism genes with measures of cognition, brain MRI phenotypes, neurological disorders (such as Alzheimer's disease or Parkinson's disease), and neuropsychiatric diseases (such as schizophrenia or obsessive-compulsive disorder).
Aim 3: To determine whether the rare coding mutations and common polymorphisms in mineral metabolism genes affect body composition and risks of developing cardiovascular diseases and other chronic diseases and conditions, including but not limited to cerebrovascular and liver diseases.
This student project will form the final chapters of my PhD dissertation. I will be mentored by my doctoral advisor, Dr. Winyoo Chowanadisai and assisted by my trainee, Aiden Y. Kim (undergraduate student) and fellow PhD students Parker R. Johnson and Cameron J. Cardona. We will disseminate our findings (summary-level only) through publication in peer-reviewed scientific journals. No generative AI will be used to analyze or be exposed to participant data.