Researcher(s)
- India Dixon, Health Behavior Science, University of Delaware
Faculty Mentor(s)
- John Jungck, Department of Mathematical Sciences, University of Delaware
Abstract
Major Depressive Disorder (MDD) remains a critical public health concern, demanding innovative strategies to optimize treatment efficacy. Despite current antidepressant therapies, achieving full recovery in MDD patients remains challenging, with only 40% experiencing remission. P-glycoprotein (P-gp), encoded by the ABCB1 gene, acts as a crucial efflux transporter in drug transport across the blood-brain barrier (BBB), thereby hindering effective drug delivery to the brain. Recent evidence indicates that P-gp may impede the uptake of specific antidepressants, thereby influencing treatment outcomes. In light of this knowledge, I aimed to investigate the discrete correlation between P-gp and remission rates concerning antidepressant treatment. To accomplish this objective, I conducted an in-depth exploration of single nucleotide polymorphisms and their correlation to the recovery of depression. Subsequently, I visualized the three dimensional structure of P-glycoprotein and analyzed evolutionary related molecules in other mammals by comparing the amino acid sequences to identify potential drug binding sites related to critical single nucleotide polymorphisms. During my investigation of the amino acid sequence, I noticed the presence of multiple methionine residues in the protein. Methionine, being an essential amino acid, serves as a critical precursor to S-adenosylmethionine (SAMe), a vital molecule involved in neurotransmitter regulation, glutathione synthesis, and essential methylation reactions implicated in MDD and other mental health disorders. Given the significance of methionine in P-gp, I propose a novel approach to increase methionine levels, potentially modulating P-gp function and enhancing antidepressant remission rates. By establishing a link between P-gp, methionine, and antidepressant efficacy, I strive to pave the way for personalized treatments in MDD and contribute to improved patient outcomes. This investigation presents a promising avenue for elevating antidepressant response rates and addressing the unmet needs of individuals suffering from treatment-resistant depression.